54 results on '"Lu, Zhen"'
Search Results
2. Quantum behaved particle swarm optimization of inbound process in an automated warehouse
- Author
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Yingying Yuan, Lu Zhen, Jingwen Wu, and Xiaofan Wang
- Subjects
Marketing ,Strategy and Management ,Management Science and Operations Research ,Management Information Systems - Published
- 2022
3. Scheduling multiple types of equipment in an automated warehouse
- Author
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Lu Zhen, Jingwen Wu, Haolin Li, Zheyi Tan, and Yingying Yuan
- Subjects
General Decision Sciences ,Management Science and Operations Research - Published
- 2022
4. Integrated berth and yard space allocation under uncertainty
- Author
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Lu Zhen, Dan Zhuge, Shuaian Wang, and Kai Wang
- Subjects
Transportation ,Management Science and Operations Research ,Civil and Structural Engineering - Published
- 2022
5. Data-driven optimization for automated warehouse operations decarbonization
- Author
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Haolin Li, Shuaian Wang, Lu Zhen, and Xiaofan Wang
- Subjects
General Decision Sciences ,Management Science and Operations Research - Published
- 2022
6. Efficient scheduling approaches to time-constrained single-armed cluster tools with condition-based chamber cleaning operations
- Author
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Fajun Yang, Chao Li, and Lu Zhen
- Subjects
Semiconductor device fabrication ,Time constrained ,business.industry ,Computer science ,Strategy and Management ,media_common.quotation_subject ,Scheduling (production processes) ,Management Science and Operations Research ,Residual ,Industrial and Manufacturing Engineering ,Wafer fabrication ,Cluster (physics) ,Quality (business) ,Process engineering ,business ,media_common - Abstract
In semiconductor manufacturing, an extremely stringent quality control is enforced for wafer fabrication processes. Consequently, cleaning operations that clear residual chemical gases and heat in ...
- Published
- 2021
7. Blockchain technology in maritime supply chains: applications, architecture and challenges
- Author
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Jiaguo Liu, Lu Zhen, and Huimin Zhang
- Subjects
0209 industrial biotechnology ,Service (systems architecture) ,021103 operations research ,Blockchain ,business.industry ,Strategy and Management ,Supply chain ,0211 other engineering and technologies ,02 engineering and technology ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,020901 industrial engineering & automation ,Heterogeneous information ,Architecture ,Telecommunications ,business - Abstract
As an essential carrier of cross-border trade, the maritime supply chain has always been plagued by long service cycles, complex structures, and heterogeneous information from multiple sources. In ...
- Published
- 2021
8. Shared mobility oriented open vehicle routing with order radius decision
- Author
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Zheyi Tan, Shuaian Wang, Wen Yi, Lu Zhen, and Junyan Lyu
- Subjects
050210 logistics & transportation ,Operations research ,Computer science ,05 social sciences ,0211 other engineering and technologies ,Mode (statistics) ,Transportation ,02 engineering and technology ,Management Science and Operations Research ,Delivery mode ,Sharing economy ,Order (exchange) ,0502 economics and business ,Vehicle routing problem ,Programming paradigm ,TRIPS architecture ,Column generation ,021108 energy ,Civil and Structural Engineering - Abstract
In the era of sharing economy and the mobility-as-service, the last mile delivery system is undergoing revolutionary changes with emerging a lot of new operation modes and policies. The crowdsourced delivery mode has become a novel and popular practice in the last mile delivery industry. This mode brings a novel way for facilitating the efficiency of last mile delivery on the basis of the shared mobility. This paper studies an open vehicle routing problem (OVRP) for the shared mobility based last mile delivery mode, in which parcel delivery orders are disseminated within a circle to attract occasional vehicles (or couriers) to fulfill these orders. Different from the traditional OVRP, this study further considers the decision of the above mentioned circle’s radius, which should be balanced between attracting enough vehicles and reducing additional cost (reward) for covering vehicles’ empty trips to the pickup location. This paper proposes a nonlinear mixed-integer programming model for the problem. A column generation based solution method is implemented to solve the model. Some numerical experiments are also conducted to validate the efficiency of the solution method and draw out some managerial implications for the practitioners. The proposed methodology in this paper may be potentially benefit not only for reducing the last mile delivery cost but also for promoting the modern transportation paradigm revolution to ridesharing and mobility-as-service.
- Published
- 2021
9. Yard truck retrofitting and deployment for hazardous material transportation in green ports
- Author
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Qian Zhang, Shuaian Wang, and Lu Zhen
- Subjects
General Decision Sciences ,Management Science and Operations Research - Published
- 2022
10. Scheduling heterogeneous delivery tasks on a mixed logistics platform
- Author
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Zheyi Tan, Junyan Lyu, Roberto Baldacci, Shuaian Wang, Lu Zhen, Zhen, Lu, Baldacci, Roberto, Tan, Zheyi, Wang, Shuaian, and Lyu, Junyan
- Subjects
Information Systems and Management ,General Computer Science ,Operations research ,Computer science ,Decision rule ,Management Science and Operations Research ,Delivery mode ,Industrial and Manufacturing Engineering ,Delivery location ,Scheduling (computing) ,Cost savings ,Or in service industriesCrowdsourced deliveryClose-open mixed multi-depot vehicle routing problemHeterogeneous fleete-commerce logistics ,Task (computing) ,Modeling and Simulation ,Column generation ,Integer programming - Abstract
Large e-commerce retailers usually establish their own logistics systems. Such systems make use of their own dedicated fleets but will also use a crowdsourced delivery mode by hiring occasional fleets. These mixed logistics systems with both dedicated and occasional fleets serve both retailers’ internal delivery tasks and external tasks requested by local businesses. This paper studies the problem of scheduling heterogeneous (internal and external) delivery tasks on a mixed logistics platform with multiple depots and two types of vehicles (dedicated and occasional). A delivery task is executed by either a dedicated vehicle or an occasional vehicle. The dedicated vehicles depart from and return to the platform's depots; the occasional vehicles depart from their original location and pick up goods from depots or external pickup locations, fulfill the delivery tasks, and finish their route at the final delivery location. We propose mixed integer programming models and column generation-based solution methods to solve the problem. A computational study is conducted based on a series of randomly generated instances and real-world instances involving 15 depots, 120 internal customers, 15 external delivery tasks, and 38 dedicated and occasional vehicles. The results obtained demonstrate the efficiency of the column generation-based solution methods. Moreover, the effectiveness of the proposed models is validated by a significant cost saving in comparison to intuitive decision rules. A sensitivity analysis is also conducted to derive a number of managerial implications.
- Published
- 2022
11. A column generation-based heuristic for a rehabilitation patient scheduling and routing problem
- Author
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Liyang Xiao, Lu Zhen, Gilbert Laporte, Roberto Baldacci, Chenghao Wang, Xiao L., Zhen L., Laporte G., Baldacci R., and Wang C.
- Subjects
Traveling salesman problem ,General Computer Science ,Rehabilitation patient scheduling ,Modeling and Simulation ,Column generation ,Time window ,Management Science and Operations Research ,Integer linear program - Abstract
Rehabilitation is an important branch of the modern healthcare system. Every day, rehabilitation patients move in hospital campus to receive treatments from therapists. The long timespan of these treatment routes leads to several patients’ complaints and results in negative effects. However, scheduling the treatment routes for patients is a complex task for hospital managers. This study investigates a rehabilitation patient scheduling and routing problem, which focuses on reducing the timespan of patients’ treatment routes. This real-life motivated problem can be described as a combination of several interrelated traveling salesman problems with time windows (TSPTWs) and is difficult to solve. We formulate the problem as an integer linear program (ILP) and we develop a greedy heuristic called “route-first, schedule-second”. Then a column generation solution method is proposed on a set partitioning-based reformulation of the original model. Specifically, a tailored genetic algorithm and several effective accelerating strategies are developed within the column generation method. Numerical experiments are conducted on 30 instances devised from real data to validate the efficiency of the proposed solution approaches. Experimental results show that our methodology can generate high-quality solutions efficiently and is therefore suitable to be applied in practice.
- Published
- 2022
12. Column generation for low carbon berth allocation under uncertainty
- Author
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Wei Zhang, Wen Yi, Qian Sun, Kai Wang, and Lu Zhen
- Subjects
Marketing ,Mathematical optimization ,021103 operations research ,Computer science ,Strategy and Management ,0211 other engineering and technologies ,chemistry.chemical_element ,Workload ,02 engineering and technology ,Management Science and Operations Research ,Management Information Systems ,chemistry ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Column generation ,Carbon ,Assignment problem - Abstract
This article investigates a low carbon-oriented berth allocation and quay crane assignment problem considering vessels’ uncertain arrival time and loading/unloading workload for vessels. A two-stag...
- Published
- 2020
13. Green technology adoption for fleet deployment in a shipping network
- Author
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Yiwei Wu, Lu Zhen, Shuaian Wang, and Gilbert Laporte
- Subjects
Operations research ,Heuristic (computer science) ,Computer science ,Control (management) ,Emission control area ,Transportation ,Context (language use) ,010501 environmental sciences ,Management Science and Operations Research ,01 natural sciences ,Scrubbers ,Order (exchange) ,0502 economics and business ,Operating cost ,0105 earth and related environmental sciences ,Civil and Structural Engineering ,Shore ,050210 logistics & transportation ,geography ,geography.geographical_feature_category ,05 social sciences ,Fleet deployment ,Green technology adoption ,Transshipment ,Liner shipping management ,Sustainability ,Software deployment ,Shore power - Abstract
The Emission Control Areas (ECAs) established by the International Maritime Organization are beneficial to reduce the sulphur emissions in maritime transportation but bring a significant increase in operating cost for shipping liners. Low sulphur emissions are required when ships berth or sail within ECAs. It is an irreversible trend that green technologies such as scrubbers and shore power will be implemented in maritime shipping industry. However, the literature lacks a quantitative decision methodology on green technology adoption for fleet deployment in a shipping network in the context of ECAs. Given a shipping network with multiple routes connected by transshipment hubs, this study proposes a nonlinear mixed integer programming model to optimally determine fleet deployment along routes (including green technology adoption), sailing speeds on all legs, timetables, cargo allocation among routes for each origin-destination pair, and berth allocation considering the availability of shore power at different berths in order to minimize total five types of cost. A three-phase heuristic is also developed to solve this problem. Numerical experiments with real-world data are conducted to validate the effectiveness of the proposed model and the efficiency of the three-phase heuristic. Some managerial implications are also outlined on the basis of the numerical experiments.
- Published
- 2020
14. Decision models for personal shopper platform operations optimization
- Author
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Lu Zhen, Xueting He, Huiwen Wang, Gilbert Laporte, and Zheyi Tan
- Subjects
Automotive Engineering ,Transportation ,Management Science and Operations Research ,Civil and Structural Engineering - Published
- 2022
15. Berth Allocation in Transshipment Ports by Considering Quay Crane Coverage and Ship Fuel Consumption
- Author
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Bochen Wang, Si Zhang, Lu Zhen, and Shucheng Yu
- Subjects
Transshipment (information security) ,Job shop scheduling ,Quay crane ,Computer science ,Range (aeronautics) ,Fuel efficiency ,Ocean Engineering ,Management Science and Operations Research ,Marine engineering - Abstract
This study investigates an integrated model for the continuous berth allocation and quay crane scheduling problem by considering quay crane coverage range, ship fuel consumption, and transshipment costs. A nonlinear mixed-integer programming model is proposed. Some nonlinear parts in this model are linearized by approximation approaches. While the objective function aims to minimize waiting costs, it also seeks to minimize fuel consumption costs from the current port to the next port and housekeeping costs generated by transshipment between vessels. A local branching-based solution algorithm is designed to solve the proposed model. Computational experiments are conducted to validate the effectiveness of the proposed scientific programming model and efficiency of the algorithm.
- Published
- 2021
16. A vehicle routing problem arising in unmanned aerial monitoring
- Author
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Miao Li, Gilbert Laporte, Wencheng Wang, and Lu Zhen
- Subjects
0209 industrial biotechnology ,021103 operations research ,General Computer Science ,Computer science ,Heuristic ,Heuristic (computer science) ,Real-time computing ,0211 other engineering and technologies ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,02 engineering and technology ,Management Science and Operations Research ,Tabu search ,Set (abstract data type) ,020901 industrial engineering & automation ,Modeling and Simulation ,Vehicle routing problem ,Routing (electronic design automation) ,Metaheuristic - Abstract
Unmanned aerial vehicles (UAVs) are widely used to perform monitoring tasks both in the military and civilian areas, and the planning of their routes is critical. This study investigates a routing problem in which UAVs monitor a set of areas with different accuracy requirements. This problem is a variant of the classical vehicle routing problem (VRP), where one must determine not only the order in which to visit a set of nodes located in the plane, but also the height at which to visit them, which impacts the accuracy level and the service time. An integer programming model is formulated to optimize flight routes and minimize the total time needed to complete the monitoring tasks. A tabu search metaheuristic is developed for the problem. Extensive numerical experiments are conducted to assess the efficiency of the heuristic.
- Published
- 2019
17. Consistent vehicle routing problem with simultaneous distribution and collection
- Author
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Kai Wang, Chengle Ma, Lu Zhen, Wenya Lv, and Ziheng Xu
- Subjects
Marketing ,Mathematical optimization ,021103 operations research ,Distribution (number theory) ,Computer science ,Strategy and Management ,0211 other engineering and technologies ,02 engineering and technology ,Reverse logistics ,Management Science and Operations Research ,Management Information Systems ,Vehicle routing problem ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing - Abstract
To improve customer service in the reverse logistics, this article defines a new variant of the vehicle routing problem (VRP) by combining the consistent VRP (ConVRP) and the VRP with simultaneous ...
- Published
- 2019
18. Hybrid electric vehicle routing problem with mode selection
- Author
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Liyang Xiao, Lu Zhen, Chengle Ma, and Ziheng Xu
- Subjects
0209 industrial biotechnology ,021103 operations research ,business.product_category ,Computer science ,Strategy and Management ,0211 other engineering and technologies ,Process (computing) ,Particle swarm optimization ,Green logistics ,02 engineering and technology ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,Automotive engineering ,020901 industrial engineering & automation ,Vehicle routing problem ,Electric vehicle ,Routing (electronic design automation) ,Hybrid vehicle ,Driving range ,business - Abstract
With the development of green logistics, logistics companies gradually are paying attention to the application of hybrid electric vehicles (HEVs). HEVs have the advantages of low energy consumption and pollution, while their disadvantage mainly lies in their limited continuous driving range. Therefore, it is necessary to optimize the use of fuel during the distribution process. We study the mode selection system in HEVs based on the background of green logistics and the above characteristics of HEVs. The mode selection system can adjust the driving mode of the HEV according to different road conditions to obtain the optimal use of fuel. In this paper, we propose a new study of a hybrid electric vehicle routing problem with mode selection. This problem is formulated as a mixed integer linear programming model. An improved particle swarm optimization algorithm (IPSO) is developed to solve this problem. Extensive numerical experiments are conducted to validate the effectiveness of the proposed model and the ...
- Published
- 2019
19. Facility location and scale optimisation in closed-loop supply chain
- Author
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Kai Wang, Lu Zhen, Xiaotian Zhang, and Qiuji Sun
- Subjects
0209 industrial biotechnology ,021103 operations research ,Scale (ratio) ,Computer science ,Strategy and Management ,Supply chain ,0211 other engineering and technologies ,02 engineering and technology ,Reverse logistics ,Management Science and Operations Research ,Decision problem ,Multi product ,Industrial engineering ,Industrial and Manufacturing Engineering ,Facility location problem ,020901 industrial engineering & automation ,Closed loop ,Remanufacturing - Abstract
This paper solves a strategic-level decision problem on determining the optimal location of (re)manufacturers and logistics centres with the consideration of facility scales in an integrated closed...
- Published
- 2019
20. Fleet deployment and demand fulfillment for container shipping liners
- Author
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Yiwei Wu, Shuaian Wang, Lu Zhen, Gilbert Laporte, and Yi Hu
- Subjects
Operations research ,Computer science ,Transportation ,010501 environmental sciences ,Management Science and Operations Research ,01 natural sciences ,Stochastic container weight ,0502 economics and business ,Revenue ,Integer programming ,0105 earth and related environmental sciences ,Civil and Structural Engineering ,Demand fulfillment ,050210 logistics & transportation ,Scale (chemistry) ,05 social sciences ,Holding cost ,Port capacity ,Fleet deployment ,Yard ,Software deployment ,Container (abstract data type) ,Fuel efficiency ,Transshipment - Abstract
This paper models and solves a fleet deployment and demand fulfillment problem for container shipping liners with consideration of the potential overload risk of containers. Given the stochastic weights of transported containers, chance constraints are embedded in the model at the strategic level. Several realistic limiting factors such as the fleet size and the available berth and yard resources at the ports are also considered. A non-linear mixed integer programming (MIP) model is suggested to optimally determine the transportation demand fulfillment scale for each origin-destination pair, as well as the ship deployment plan along each route, with an objective incorporating revenue, fixed operation cost, fuel consumption cost, holding cost for transhipped containers, and extra berth and yard costs. Two efficient algorithms are then developed to solve the non-linear MIP model for different instance sizes. Numerical experiments based on real-world data are conducted to validate the effectiveness of the model and the algorithms. The results indicate the proposed methodology yields solutions with an optimality gap less than about 0.5%, and can solve realistic instances with 19 ports and four routes within about one hour.
- Published
- 2019
21. A Decision Framework for Automatic Guided Vehicle Routing Problem with Traffic Congestions
- Author
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Yiwei Wu, Qiuji Sun, Lu Zhen, Qi Yue, and Si Zhang
- Subjects
Queueing theory ,021103 operations research ,Computer science ,Computation ,Distributed computing ,0211 other engineering and technologies ,010103 numerical & computational mathematics ,02 engineering and technology ,Management Science and Operations Research ,01 natural sciences ,Scheduling (computing) ,Vehicle routing problem ,Traffic conditions ,0101 mathematics ,Lattice graph - Abstract
Automatic guided vehicles are widely used in various types of warehouses including the automated container terminals. This paper provides a decision framework for port managers to design and schedule automatic guided vehicle routing plans under time-varying traffic conditions. A large number of computational experiments on a grid graph are conducted to validate the efficiency of the proposed decision framework. We also proposed one efficient queueing rule in automatic guided vehicle routing scheduling. Although the complexity of the problem is high, computational results show that our proposed decision framework can provide high quality solutions within a relatively short computation time.
- Published
- 2018
22. Subsidy design in a vessel speed reduction incentive program under government policies
- Author
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Lu Zhen, Shuaian Wang, Dan Zhuge, and Gilbert Laporte
- Subjects
Public policy ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Ocean Engineering ,Management Science and Operations Research ,Profit (economics) ,Modelling and Simulation ,Incentive program ,Green transportation ,Tax policy ,Finance ,Government ,air emission taxes ,business.industry ,subsidy game ,vessel speed reduction incentive program ,Subsidy ,sharing subsidy ,Port (computer networking) ,green port and shipping ,Sustainability ,Modeling and Simulation ,Economic interventionism ,Business - Abstract
As a green port and shipping-related policy, the vessel speed reduction incentive program (VSRIP) involves using a subsidy to induce ships to reduce their speed in a port area so that the emissions can be reduced at the port. However, this program may attract new ships to visit the port because of the subsidy; in this case, the port's profit will grow due to more ship visits, but its total emissions may also increase, which is counter to the original intention of the subsidy. The government could then intervene by providing part of the subsidy for the VSRIP or by collecting air emission taxes for the increased emission at the port. This paper studies how to design suitable subsidies for ships participating in a VSRIP. Two bilevel subsidy design models are formulated based on a Stackelberg game to maximize the port's profit (related to the profits from original and new ships, the subsidy provided by the port, and air emission taxes) and to minimize the government's cost (related to the damage cost of air emissions, the subsidy provided by the government, and air emission taxes). We determine which policy (including a sharing subsidy policy, no government intervention, and an air emission tax policy) should be implemented by the government in different cases and how much subsidy should be provided by the port under each government policy. We find that these decisions are affected by several practical factors, such as the damage cost of air emissions per ton of fuel and the subsidy sensitivities of original and new ships. We also outline several meaningful insights based on the analysis of these practical factors.
- Published
- 2021
23. A Heuristic Algorithm for solving a large-scale real-world territory design problem
- Author
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Lu Zhen, Marco Antonio Boschetti, Andrew Lim, Roberto Baldacci, Lin Zhou, Ying Dai, Zhou, Lin, Zhen, Lu, Baldacci, Roberto, Boschetti, Marco, Dai, Ying, and Lim, Andrew
- Subjects
Service (systems architecture) ,Information Systems and Management ,Operations research ,Computer science ,Heuristic (computer science) ,Strategy and Management ,media_common.quotation_subject ,Scale (chemistry) ,Management Science and Operations Research ,Work (electrical) ,Genetic algorithm ,Territory designPeriodic vehicle routingHybrid genetic algorithmDairy industryReal-world instances ,Routing (electronic design automation) ,Function (engineering) ,Fixed cost ,media_common - Abstract
In this work, we present and evaluate heuristic techniques for a real-world territory design problem of a major dairy company which produces and distributes perishable products. The problem calls for grouping customers into geographic districts, with the objective of minimising the total operational cost, computed as a function of the fixed costs of the districts and the routing costs. Two inter-connected decision levels have to be tackled: partitioning customers into districts and routing vehicles according to complex operational constraints. To solve the problem, a hybrid multi-population genetic algorithm is designed, enhanced with several evolution and search techniques. The proposed design is extensively tested on instances derived from the literature and on real-world large-scale instances, involving more than 1000 customers. The results show the effectiveness of the different components of the algorithm and the feedback from the company’s planners confirms that it produces high-quality, operational solutions. Additionally, we explore some managerial findings with respect to the adoption of alternative objectives and service requirements.
- Published
- 2021
24. Schedule design for liner services under vessel speed reduction incentive programs
- Author
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Gilbert Laporte, Shuaian Wang, Dan Zhuge, and Lu Zhen
- Subjects
Schedule ,Mathematical optimization ,speed limit ,VSRIP ,Speed limit ,enumerative algorithm ,Ocean Engineering ,piecewise-linear approximation ,Management Science and Operations Research ,Sustainability ,liner shipping ,Modeling and Simulation ,Modelling and Simulation ,Environmental science ,Incentive program ,Speed reduction ,schedule design ,Green transportation ,Liner shipping ,Piecewise linear approximation - Abstract
Gas and particulate emissions from ship transportation have been increasing in recent years. In order to mitigate ship emissions near coastal areas, voluntary vessel speed reduction incentive programs (VSRIPs) were put in place by a number of ports. This paper studies a schedule design problem faced by liner shipping companies under VSRIPs. It proposes a mixed-integer nonlinear mathematical model for the minimization of the total cost, consisting of fuel cost, as well as operating cost, minus dockage refunds. The model balances three determinants, that is, the compliance of VSRIPs, the speed limit (the maximum physical speed of ships and the upper speed limit imposed by VSRIPs), and the limited number of ships. An enumerative algorithm and a piecewise-linear approximation algorithm are developed, based on some properties of the nonlinear model. The efficiency of the proposed algorithms is validated through extensive computational experiments.
- Published
- 2020
25. Dynamic programming algorithms for selection of waste disposal ports in cruise shipping
- Author
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Dan Zhuge, Lu Zhen, and Shuaian Wang
- Subjects
050210 logistics & transportation ,Water transport ,Stochastic modelling ,Computer science ,05 social sciences ,Cruise ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Transportation ,010501 environmental sciences ,Management Science and Operations Research ,Dispose pattern ,01 natural sciences ,Computer Science::Robotics ,Dynamic programming ,0502 economics and business ,Key (cryptography) ,Algorithm ,Selection (genetic algorithm) ,0105 earth and related environmental sciences ,Civil and Structural Engineering ,Waste disposal - Abstract
The cruise industry has maintained a steady growth in the past 20 years. Due to the large number of cruise passengers and regulations on sea environment protection, determining at which ports to dispose of the waste generated onboard a cruise ship is a key decision to reduce the cost for a cruise company. We address four versions of the problem: the cruise itinerary is either static or dynamic and the amount of waste generated on each voyage leg is either deterministic or stochastic. We propose a polynomial-time solution algorithm for the static deterministic model, and the idea of the algorithm can also be used to solve the static stochastic model and the dynamic deterministic model. Second, we identify the structure of the optimal policy to the dynamic stochastic problem, based on which an efficient dynamic programming algorithm is developed. Extensive numerical experiments derived from problems of real-case scales demonstrate the efficiency of the proposed algorithms.
- Published
- 2018
26. Task assignment and sequencing decision model under uncertain available time of service providers
- Author
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Xin Shi, Lufei Huang, Yi Hu, Lu Zhen, and Hao Hao
- Subjects
Marketing ,050210 logistics & transportation ,021103 operations research ,Basis (linear algebra) ,Operations research ,Computer science ,Heuristic ,Strategy and Management ,05 social sciences ,0211 other engineering and technologies ,02 engineering and technology ,Management Science and Operations Research ,Decision problem ,Service provider ,Stochastic programming ,Management Information Systems ,Task (project management) ,0502 economics and business ,Decision model ,Finite set - Abstract
This paper studies an integrated decision problem on assigning and sequencing tasks to service providers. By considering the uncertain available time of the service providers, a stochastic programming model is proposed on the basis of a finite set of scenarios. Some realistic factors are also taken into account and formulated as some non-linear cost functions, which are linearised in this study. Moreover, a heuristic solution method is designed for solving some extremely large-scale problem cases within a reasonable period of time. Numerical experiments are performed to validate the effectiveness of the proposed model and the efficiency of the proposed solution method.
- Published
- 2018
27. Berth assignment for liner carrier clusters under a cooperative environment
- Author
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Yulong Sun, Jianfeng Zheng, Lu Zhen, Wencheng Han, Fanwen Meng, and Lingxiao Yang
- Subjects
Queueing theory ,Mathematical optimization ,General Computer Science ,Berth allocation problem ,Computer science ,Modeling and Simulation ,Stability (learning theory) ,Core theory ,Programming paradigm ,Binary number ,Management Science and Operations Research ,Stage ii ,Cluster analysis - Abstract
The berth allocation problem (BAP) has been extensively studied in the literature, which seeks to determine berths and times for upcoming ships. The previous studies do not distinguish berths and ships among different liner carriers. By taking into account the increasing use of dedicated berths in practice, this paper proposes a special BAP where berths and ships could be distinguished among different liner carriers. For our BAP under a cooperative environment, we propose a mixed-integer programming model. Based on an assignment model with binary variables, our BAP can be reduced to the liner carrier clustering problem. To generate stable liner carrier clusters used in our assignment model, queueing theory and core theory are applied. A three-stage optimization method is proposed to solve our BAP. Namely, stage I proposes a queueing theory approach for various liner carrier clusters, and based on core theory stage II determines the stability of different liner carrier clusters. Based on the results obtained in stages I and II, stage III solves the liner carrier clustering problem. Numerical experiments are carried out to demonstrate the effectiveness of the proposed method.
- Published
- 2021
28. Improved Benders decomposition for stochastic yard template planning in container terminals
- Author
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Hongtao Hu, Jiao Mo, and Lu Zhen
- Subjects
Truck ,Operations research ,Computer science ,Transportation ,Management Science and Operations Research ,Port (computer networking) ,Stochastic programming ,Scheduling (computing) ,Yard ,Terminal (electronics) ,Traffic congestion ,Automotive Engineering ,Container (abstract data type) ,Civil and Structural Engineering - Abstract
Recent trends in pursuing green ports have had positive effects on terminal operators constructing more eco-friendly decision schemes. A yard template in a container port not only determines the scheduling of the terminal handling equipment by container allocation, but also affects the carbon emissions from yard trucks caused by loading and unloading operations, due to the differing degree of yard road congestion. Moreover, the uncertainty regarding the number of transporting containers makes it challenging to construct a robust yard template for a container terminal. Motivated by research pointing to the need to alleviate the exhaust pollution generated by port handling equipment, this paper presents a two-stage stochastic programming model for yard template planning, with the aim of minimizing the maintenance and manpower costs of activating yard cranes for container handling and of reducing the carbon dioxide emitted from yard trucks. More specifically, the paper considers the impact of road congestion on carbon dioxide emissions from the perspective of the increase in transportation time caused by yard truck interruptions. The uncertainty regarding the number of transport containers is reflected by taking into account numerous scenarios in which different numbers of containers are loaded onto (discharged from) vessels that visit the port periodically. In addition, an improved Benders decomposition-based solution method is designed to solve the proposed model with large-scale problem instances. Several experiments are performed to validate the effectiveness of the model and the efficiency of the method. The numerical results demonstrate that yard template planning that considers road congestion can effectively reduce the carbon emissions of yard trucks in loading and unloading operations.
- Published
- 2021
29. Daily berth planning in a tidal port with channel flow control
- Author
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Ek Peng Chew, Dan Zhuge, Loo Hay Lee, Zhe Liang, and Lu Zhen
- Subjects
050210 logistics & transportation ,Mathematical optimization ,021103 operations research ,Computer science ,05 social sciences ,Control (management) ,0211 other engineering and technologies ,Transportation ,02 engineering and technology ,Management Science and Operations Research ,Port (computer networking) ,Open-channel flow ,Set (abstract data type) ,Test case ,0502 economics and business ,Column generation ,Assignment problem ,Decision model ,Civil and Structural Engineering ,Marine engineering - Abstract
This paper studies an operational-level berth allocation and quay crane assignment problem (daily berth planning) considering tides and channel flow control constraints. An integer programming model is proposed for this problem. Then a column generation solution approach is developed on a set partitioning based reformulation of the original model. Computational study is conducted on 30 test cases constructed from real-world data to validate efficiency of the proposed solution approach. Results show that this simple but practical solution approach can optimally solve the daily berthing planning problem instances with up to 80 vessels, 40 berths, and 120 quay cranes within one hour, which is reasonable and acceptable for the real-world applications. The proposed decision model and the solution approach could be potentially useful for some tidal ports with (or without) navigation channels.
- Published
- 2017
30. Production stage allocation problem in large corporations
- Author
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Sheng Lei Zhu, Dan Zhuge, and Lu Zhen
- Subjects
050210 logistics & transportation ,Mathematical optimization ,021103 operations research ,Information Systems and Management ,Operations research ,business.industry ,Strategy and Management ,05 social sciences ,0211 other engineering and technologies ,Automotive industry ,Scheduling (production processes) ,Particle swarm optimization ,02 engineering and technology ,Management Science and Operations Research ,Decision problem ,Diseconomies of scale ,Stochastic programming ,0502 economics and business ,Economics ,Revenue ,Fixed cost ,business - Abstract
This paper studies a strategic-level decision problem on assigning production stages to geographically distributed subsidiaries in a large corporation so as to minimize the fixed cost and the expected value of the production/transportation costs under stochastic demands of customers. The influence of the economies and diseconomies of scale on unit production cost is considered. A nonlinear mixed integer programming model is designed for this problem. A local branching based solution method and a particle swarm optimization based solution method are developed for solving the model. Computational tests on real world data of Shanghai Volkswagen Auto Corp. are conducted. The results show that the proposed model can save about 2.5% of its revenue by comparing with the current decisions.
- Published
- 2017
31. Analysis of three container routing strategies
- Author
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Lu Zhen, Dan Zhuge, and Shuaian Wang
- Subjects
050210 logistics & transportation ,Economics and Econometrics ,021103 operations research ,Operations research ,05 social sciences ,0211 other engineering and technologies ,02 engineering and technology ,Management Science and Operations Research ,General Business, Management and Accounting ,Industrial and Manufacturing Engineering ,Profit (economics) ,0502 economics and business ,Economics ,Heuristic routing ,Liner shipping - Abstract
As containers need several weeks to be delivered to their destinations and the future container shipment demand is uncertain, a myopic strategy for container routing that maximizes the immediate profit may lead to insufficient remaining capacity for transporting more profitable containers in the future. This study conducts a theoretical analysis to compare three container routing strategies, i.e., (i) a widely used myopic strategy, (ii) a non-myopic heuristic routing strategy that incorporates information about the future demand distribution, and (iii) a strategy that assumes future demand is known. Then a practical non-myopic heuristic container routing strategy is developed for practical purposes to increase the profit of liner shipping companies. Extensive numerical experiments show that the proposed non-myopic heuristic container routing strategy brings in an extra of 2%–3% profit over the myopic strategy.
- Published
- 2017
32. Preface: Advance Analytics in Maritime Systems
- Author
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Lu Zhen
- Subjects
Engineering ,business.industry ,Analytics ,Ocean Engineering ,Management Science and Operations Research ,business ,Data science - Published
- 2021
33. Crowdsourcing mode evaluation for parcel delivery service platforms
- Author
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Yiwei Wu, Wen Yi, Shuaian Wang, and Lu Zhen
- Subjects
Flexibility (engineering) ,Economics and Econometrics ,Service (systems architecture) ,021103 operations research ,Computer science ,business.industry ,05 social sciences ,0211 other engineering and technologies ,Mode (statistics) ,02 engineering and technology ,E-commerce ,Management Science and Operations Research ,Crowdsourcing ,General Business, Management and Accounting ,Data science ,Maturity (finance) ,Industrial and Manufacturing Engineering ,Task (project management) ,Competition (economics) ,0502 economics and business ,business ,050203 business & management - Abstract
The fast-growing practice of e-commerce implies a strong increase in the urban parcel delivery, which in turn creates significant pressure on last-mile city logistics. Because the crowdsourced delivery offers greater flexibility and requires less capital investment than traditional delivery methods, it has been playing a more crucial role when faced with the growing demand for the urban parcel delivery. With the increasing maturity of the crowdsourced delivery and the fierce competition among platforms, the evaluation of different crowdsourcing modes for the urban parcel delivery becomes important. This study proposes six mathematical models to evaluate different operation modes of the crowdsourced delivery in a quantitative way. Several realistic factors, such as the latest service time for each task, task cancellation rate and range distribution of tasks, are also analyzed in this paper. Numerical experiments are conducted to validate the effectiveness of the proposed models and to analyze the impact of different modes. Some managerial implications are also outlined on the basis of the numerical experiments and sensitivity analysis to help crowdsourced companies to make scientific decisions.
- Published
- 2021
34. A two-stage decomposition method on fresh product distribution problem
- Author
-
Hongtao Hu, Lu Zhen, and Ye Zhang
- Subjects
050210 logistics & transportation ,Mathematical optimization ,Engineering ,021103 operations research ,Job shop scheduling ,Heuristic (computer science) ,business.industry ,Strategy and Management ,05 social sciences ,0211 other engineering and technologies ,Refrigerator car ,Particle swarm optimization ,02 engineering and technology ,Energy consumption ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,0502 economics and business ,Shortest path problem ,Vehicle routing problem ,Decomposition method (constraint satisfaction) ,business - Abstract
Refrigerator cars are widely used for fresh product distribution. The energy consumption of these vehicles is sensitive to the environment temperature, and changes continuously due to fluctuations of the environment temperature. As a result, the total refrigeration cost is influenced by the car’s departure time. To reduce operation costs of third-party transportation providers, the refrigerator car scheduling problem is addressed in this research. A time-dependent mixed-integer programming model is established to reduce total operation costs, including routing, time penalty, cargo damage and refrigeration costs. An adaptive heuristic method is proposed by combining the variable neighbourhood search and particle swarm optimisation. To improve the algorithm quality, a two-stage decomposition method is developed. The problem is divided into two echelon sub-problems. One is the shortest path problem, and the other is the departure time scheduling problem. A feedback strategy is utilised to avoid local optimal...
- Published
- 2017
35. Cruise service planning considering berth availability and decreasing marginal profit
- Author
-
Kai Wang, Lu Zhen, Xiaobo Qu, and Shuaian Wang
- Subjects
050210 logistics & transportation ,Engineering ,Mathematical optimization ,021103 operations research ,Marginal profit ,Operations research ,business.industry ,Logistics & Transportation ,05 social sciences ,Cruise ,0211 other engineering and technologies ,Transportation ,Time horizon ,02 engineering and technology ,Management Science and Operations Research ,Nonlinear programming ,Network planning and design ,0502 economics and business ,business ,Greedy algorithm ,Decision model ,Integer programming ,Civil and Structural Engineering - Abstract
© 2016 Elsevier Ltd This paper addresses a decision problem on planning cruise services for a cruise ship so as to maximize the total profit during a planning horizon. The service is a sequence of ports (harbor cities) that the cruise ship visits. In this decision problem, the constraint about the availability of berths at each port is taken into account. In reality, if a cruise service is executed by the ship repeatedly for several times, the profit earned by the cruise service in each time decreases gradually. This effect of decreasing marginal profit is also considered in this study. We propose a nonlinear integer programming model to cater to the concavity of the function for the profit of operating a cruise service repeatedly. To solve the nonlinear model, two linearization methods are developed, one of which takes advantage of the concavity for a tailored linearization. Some properties of the problem are also investigated and proved by using the dynamic programming (DP) and two commonly used heuristics. In particular, we prove that if there is only one candidate cruise service, a greedy algorithm can derive the optimal solution. Numerical experiments are conducted to validate the effectiveness of the proposed models and the efficiency of the proposed linearization methods. In case some parameters needed by the model are estimated inexactly, the proposed decision model demonstrates its robustness and can still obtain a near-optimal plan, which is verified by experiments based on extensive real cases.
- Published
- 2017
36. Multi-period yard template planning in container terminals
- Author
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Zhou Xu, Kai Wang, Yi Ding, and Lu Zhen
- Subjects
Truck ,050210 logistics & transportation ,Engineering ,Mathematical optimization ,021103 operations research ,business.industry ,05 social sciences ,0211 other engineering and technologies ,Particle swarm optimization ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Transportation ,02 engineering and technology ,Decision rule ,Management Science and Operations Research ,Port (computer networking) ,Yard ,Traffic congestion ,0502 economics and business ,Container (abstract data type) ,business ,Integer programming ,Simulation ,Civil and Structural Engineering - Abstract
This paper is about yard management in container ports. As a tactical level decision-making tool in a port, a yard template determines the assignment of spaces (subblocks) in a yard for arriving vessels, which visit the port periodically. The objective of yard template planning is to minimize the transportation cost of moving containers around the yard. To handle yard template planning, a mixed integer programming model is proposed that also takes into account traffic congestion in the yard. A further complication is that the cycle time of the vessels' periodicities is not uniform and varies among them, perhaps being one week, ten days, or two weeks, etc. However, this multiple cycle time of the periodicities of vessel arrival patterns, which complicates the yard template decision, is also considered in the model. Moreover, a local branching based solution method and a Particle Swarm Optimization based solution method are developed for solving the model. Numerical experiments are also conducted to validate the effectiveness of the proposed model, which can save around 24% of the transportation costs of yard trucks when compared with the commonly used First-Come-First-Served decision rule. Moreover, the proposed solution methods can not only solve the proposed model within a reasonable time, but also obtain near-optimal results with about 0.1–2% relative gap.
- Published
- 2016
37. Scheduling quay cranes and yard trucks for unloading operations in container ports
- Author
-
Lu Zhen, Zhuo Sun, Shucheng Yu, and Shuaian Wang
- Subjects
Truck ,021103 operations research ,Optimization problem ,Computational complexity theory ,Job shop scheduling ,Computer science ,0211 other engineering and technologies ,General Decision Sciences ,Particle swarm optimization ,02 engineering and technology ,Management Science and Operations Research ,Solver ,Scheduling (computing) ,Genetic algorithm ,Programming paradigm ,Simulation - Abstract
This paper studies an integrated optimization problem on quay crane and yard truck scheduling in container terminals. A mixed-integer programming model is formulated. For the model, we show the integrated scheduling problem is strongly NP-hard and investigate some properties that can considerably reduce the computational complexity. For solving the proposed model within a reasonable time, a particle swarm optimization based solution method is developed. Numerical experiments are conducted to compare the proposed method with the CPLEX solver and the genetic algorithm. The results validate the effectiveness of the proposed model and the efficiency of the proposed solution method.
- Published
- 2016
38. Terminal allocation problem in a transshipment hub considering bunker consumption
- Author
-
Kai Wang, Lu Zhen, and Shuaian Wang
- Subjects
Consumption (economics) ,050210 logistics & transportation ,Mathematical optimization ,021103 operations research ,Transshipment (information security) ,Computer science ,05 social sciences ,0211 other engineering and technologies ,Particle swarm optimization ,Ocean Engineering ,02 engineering and technology ,Decision rule ,Management Science and Operations Research ,Port (computer networking) ,Bunker ,Terminal (electronics) ,First-come, first-served ,Modeling and Simulation ,0502 economics and business ,Operations management - Abstract
This article investigates the method of allocating arriving vessels to the terminals in transshipment hubs. The terminal allocation decision faced by a shipping alliance has the influence on the scheduled arrival time of vessels and further affects the bunker consumption cost for the vessels. A model is formulated to minimize the bunker consumption cost as well as the transportation cost of inter-terminal transshipment flows/movements. The capacity limitation of the port resources such as quay cranes (QCs) and berths is taken into account. Besides the terminal allocation, the QC assignment decision is also incorporated in the proposed model. A local branching based method and a particle swarm optimization based method are developed to solve the model in large-scale problem instances. Numerical experiments are also conducted to validate the effectiveness of the proposed model, which can save around 14% of the cost when compared with the “First Come First Served” decision rule. Moreover, the proposed solution methods not only solve the proposed model within a reasonable computation time, but also obtain near-optimal results with about 0.1∼0.7% relative gap. © 2016 Wiley Periodicals, Inc. Naval Research Logistics 63: 529–548, 2016
- Published
- 2016
39. The Joint quay crane scheduling and block allocation problem in container terminals
- Author
-
Chengle Ma, Xiaotian Zhang, Xiazhong Chen, Lu Zhen, and Hongtao Hu
- Subjects
050210 logistics & transportation ,Mathematical optimization ,021103 operations research ,Quay crane ,Computer science ,Applied Mathematics ,Strategy and Management ,05 social sciences ,0211 other engineering and technologies ,02 engineering and technology ,Management Science and Operations Research ,Management Information Systems ,Scheduling (computing) ,Modeling and Simulation ,Block (telecommunications) ,0502 economics and business ,Container (abstract data type) ,Joint (building) ,General Economics, Econometrics and Finance - Published
- 2018
40. Data-Driven Intelligent Port Management Based on Blockchain
- Author
-
Maria Attard, Lu Zhen, Shuaian Wang, and Liyang Xiao
- Subjects
050210 logistics & transportation ,Government ,021103 operations research ,Blockchain ,Computer science ,business.industry ,05 social sciences ,0211 other engineering and technologies ,Ocean Engineering ,02 engineering and technology ,Management Science and Operations Research ,Port (computer networking) ,Data-driven ,0502 economics and business ,Port management ,Telecommunications ,business - Abstract
This paper proposes a blockchain-based framework to improve the efficiency of ship traffic in port. In the framework, ship agents, terminals, tug company, pilot station, and government share information and the information is stored in a blockchain. Based on the shared information, we discuss three categories of data-driven models that can improve the operations management of the above five parties. The first category is decisions made by a single party. The second category involves decisions of at least two ship agents. The third category relates to multi-party decision-making under uncertainty. This study hopes to stimulate maritime practitioners to embrace blockchain technology and data-driven approaches to enhance the competitiveness of the industry.
- Published
- 2020
41. Modeling of yard congestion and optimization of yard template in container ports
- Author
-
Lu Zhen
- Subjects
Truck ,050210 logistics & transportation ,Engineering ,021103 operations research ,Operations research ,business.industry ,05 social sciences ,0211 other engineering and technologies ,Probabilistic logic ,ComputerApplications_COMPUTERSINOTHERSYSTEMS ,Transportation ,Context (language use) ,02 engineering and technology ,Management Science and Operations Research ,Yard ,Traffic congestion ,0502 economics and business ,Container (abstract data type) ,Programming paradigm ,business ,Integer programming ,Simulation ,Civil and Structural Engineering - Abstract
As a tactical-level plan, a yard template determines the assignment of spaces in a container port yard for arriving vessels. This paper investigates the concept of yard congestion quantitatively in the context of yard truck interruptions, and develops a combination of probabilistic and physics-based models for truck interruptions. The above work enables us to exactly evaluate the expected link travel time, which then acts as the basis for proposing a mixed-integer programming model that minimizes the total expected travel time of moving containers around the yard. A Squeaky Wheel Optimization based meta-heuristic is developed to solve the model. Experiments are also conducted to validate the effectiveness of the model and the solution method.
- Published
- 2016
42. Quay crane scheduling problem with considering tidal impact and fuel consumption
- Author
-
Shucheng Yu, Lu Zhen, and Shuaian Wang
- Subjects
050210 logistics & transportation ,Mathematical optimization ,021103 operations research ,Job shop scheduling ,Quay crane ,Computer science ,05 social sciences ,0211 other engineering and technologies ,Particle swarm optimization ,02 engineering and technology ,Management Science and Operations Research ,Port (computer networking) ,Industrial and Manufacturing Engineering ,Nonlinear programming ,Nonlinear system ,0502 economics and business ,Fuel efficiency ,Simulation - Abstract
This study investigates a quay crane scheduling problem with considering the impact of tides in a port and fuel consumption of ships. A mixed-integer nonlinear programming model is proposed. Some nonlinear parts in the model are linearized by approximation approaches. For solving the proposed model in large-scale problem instances, both a local branching based solution method and a particle swarm optimization based solution method are developed. Numerical experiments with some real-world like cases are conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution methods.
- Published
- 2016
43. Models on ship scheduling in transshipment hubs with considering bunker cost
- Author
-
Tao Shen, Lu Zhen, Shuaian Wang, and Shucheng Yu
- Subjects
050210 logistics & transportation ,Economics and Econometrics ,021103 operations research ,Operations research ,Computer science ,05 social sciences ,0211 other engineering and technologies ,Scheduling (production processes) ,02 engineering and technology ,Management Science and Operations Research ,Decision problem ,General Business, Management and Accounting ,Industrial and Manufacturing Engineering ,Transshipment ,Bunker ,0502 economics and business ,Integer programming - Abstract
This paper studies a decision problem for scheduling ships׳ starting operation time in a transshipment hub with considering the bunker cost and the transshipment cost of containers. Based on the information about the handing capacity of the container port in each period, the port operator makes a proper decision and informs the shipping companies about the start operation days of each liner route. The optimized decision may help shipping companies significantly reduce the cost. This study proposes a mixed integer programming model. The NP-hardness of the problem is proved. A local branching based solution method is also developed for solving the model. Extensive numerical experiments demonstrate the optimality of the solution by the proposed method is less than 3% for large-scale problem instances.
- Published
- 2016
44. Tactical berth allocation under uncertainty
- Author
-
Lu Zhen
- Subjects
Mathematical optimization ,Information Systems and Management ,General Computer Science ,Operations research ,Stochastic modelling ,Computer science ,Management Science and Operations Research ,Industrial and Manufacturing Engineering ,Stochastic programming ,Scheduling (computing) ,Dwell time ,Berth allocation problem ,Modeling and Simulation ,Probability distribution - Abstract
The tactical berth allocation problem (BAP) concerns the allocation of favorite berthing positions to ships that periodically call at the terminals. This paper investigates the tactical-level berth allocation scheduling models. First a deterministic model for tactical BAP is formulated with considering the periodicity of schedule. However, in reality, the number of containers that need to be handled (discharging & loading) for each ship is uncertain in the ship's future periods. Thus for the tactical BAP, there is significant uncertainty with respect to the operation time (dwell time) of ships, which further complicates the traditional berth allocation decisions. From stochastic perspective, this paper proposes both a stochastic programming formulation that can cope with arbitrary probability distributions of ships’ operation time deviation, and a robust formulation that is applicable to situations in which limited information about probability distributions is available. The relationship between the two models is also investigated in an analytic way. Some meta-heuristic algorithms are suggested for solving the models. Numerical experiments are performed to validate the effectiveness of the proposed models and the efficiency of the proposed solution algorithms. The experiments also compare the above stochastic programming formulation and the robust formulation models, as well as evaluate their potential benefits in practice. This study finds that the robust method can derive a near optimal solution to the stochastic model in a fast way, and also has the benefit of limiting the worst-case outcome of the tactical BAP decisions.
- Published
- 2015
45. Tug scheduling for hinterland barge transport: A branch-and-price approach
- Author
-
Xiaobo Qu, Kai Wang, Lu Zhen, and Shuaian Wang
- Subjects
050210 logistics & transportation ,geography ,Operations Research ,021103 operations research ,Information Systems and Management ,geography.geographical_feature_category ,General Computer Science ,Operations research ,Computer science ,Branch and price ,05 social sciences ,BARGE ,0211 other engineering and technologies ,Scheduling (production processes) ,02 engineering and technology ,Management Science and Operations Research ,Flow network ,Industrial and Manufacturing Engineering ,Modeling and Simulation ,0502 economics and business ,River mouth - Abstract
© 2017 Elsevier B.V. In a hinterland barge transport system, barges are usually not self-propelled and need to be towed or pushed by tugs. This study investigates a tug-scheduling problem at a seaport that is located at a river mouth and that connects the hinterland ports along the river with the global maritime transportation network. A mixed-integer programming model is proposed to optimize the assignment of barges to tugs as well as the time when the tugs depart from the seaport and go to the hinterland ports. Some properties of the model are also investigated. Moreover, an exact solution method based on a branch-and-price approach is developed to solve the proposed model. Numerical experiments are also conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution method.
- Published
- 2018
46. Task assignment under uncertainty: stochastic programming and robust optimisation approaches
- Author
-
Lu Zhen
- Subjects
Linear bottleneck assignment problem ,Mathematical optimization ,business.industry ,Computer science ,Strategy and Management ,Management Science and Operations Research ,Machine learning ,computer.software_genre ,Industrial and Manufacturing Engineering ,Stochastic programming ,Task (project management) ,Probability distribution ,Artificial intelligence ,business ,computer ,Assignment problem ,Generalized assignment problem ,Software project management ,Weapon target assignment problem - Abstract
The assignment of tasks to teams is a challenging combinatorial optimisation problem. The uncertainty in the tasks’ execution processes further complicates the assignment decisions. This study investigates a variant of the typical assignment problem, in which each task can be divided into two parts, one is deterministic and the other is uncertain with respect to their workloads. From the stochastic perspective, this paper proposes both a stochastic programming model that can cope with arbitrary probability distributions of tasks’ random workload requirements, and a robust optimisation model that is applicable to situations in which limited information about probability distributions is available. An example of its application in the software project management is given. Some numerical experiments are also performed to validate the effectiveness of the proposed models and the relationships between the two models.
- Published
- 2014
47. Collaborative stowage planning problem for a liner ship
- Author
-
Lu Zhen, Wen Yi, Yi Hu, Wencheng Wang, and Miao Li
- Subjects
Sequence ,Mathematical optimization ,Quay crane ,Computer science ,Particle swarm optimization ,Transportation ,Management Science and Operations Research ,Stochastic programming ,Maritime logistics ,Management of Technology and Innovation ,Stowage ,Business and International Management ,Decision model ,Liner shipping - Abstract
This paper investigates a stowage planning problem, in which a liner ship will visit a sequence of ports, the number of available quay cranes in ports and the numbers of loading/unloading containers in ports are uncertain. This stowage planning problem is about how to assign the loaded containers to the bays of the ship considering uncertain information in the future, so as to minimise the sum of the expected quay crane handling time at the ports. Based on stochastic programming, a two-stage decision model is proposed for this problem. A particle swarm optimisation based solution method is developed to solve the model for large-scale problem instances. Numerical experiments are conducted to validate the effectiveness of the proposed model and the efficiency of the proposed solution method.
- Published
- 2019
48. A method for estimating liner shipping time under uncertainty
- Author
-
Hao Hao, Miao Li, Min Lin, and Lu Zhen
- Subjects
Operations research ,Computer science ,Process (computing) ,Transportation ,Probability and statistics ,Management Science and Operations Research ,Port (computer networking) ,Set (abstract data type) ,Terminal (electronics) ,Management of Technology and Innovation ,Container (abstract data type) ,Probability distribution ,Business and International Management ,Transit (satellite) - Abstract
With the rapid development of container transportation and the fierce competition among ports, container terminal operators pay more attention to meet the individual needs of customers. This study develops a system to estimate container liner shipping arrival time and the probability distribution for each time set by considering transit process and the periodicity of liner shipping. This system can give the most possible arrival time of cargoes to customers in advance, and then improve the level of port services. Also, a recursive algorithm based solution method and a parallel computing based solution method are proposed for solving the problem. Computational test is conducted on different scales and the results show the effectiveness of the proposed solution approach.
- Published
- 2019
49. A design of knowledge management tool for supporting product development
- Author
-
Jian-Guo Li, Lu Zhen, and Lin Wang
- Subjects
Descriptive knowledge ,Knowledge management ,business.industry ,Computer science ,Knowledge engineering ,Knowledge value chain ,Library and Information Sciences ,Management Science and Operations Research ,Knowledge acquisition ,Computer Science Applications ,Knowledge sharing ,Knowledge-based systems ,Media Technology ,Personal knowledge management ,Domain knowledge ,business ,Information Systems - Abstract
New Product Development (NPD) is one of the most important activities for companies. The NPD activities get to depend on knowledge more and more. Therefore, Knowledge Management (KM) has become a key issue and a hot topic in the fields of NPD researches. This paper proposes a new design of an effective NPD-support KM tool for facilitating the knowledge sharing and acquisition among collaborative NPD team members. The KM tool mainly contains two channels for knowledge acquisition: knowledge query and knowledge recommendation. The former one is the basic function for all types of KM tools, and also acts as the basis for the latter one. This paper proposes two types of knowledge recommendation ways: one is a vector-based way; the other is a phrase-based way. Key techniques for implementing the KM tool are elaborated. A demo example is also illustrated to show the functions of the proposed KM tool.
- Published
- 2013
50. An analytical study on service-oriented manufacturing strategies
- Author
-
Lu Zhen
- Subjects
Economics and Econometrics ,Service (systems architecture) ,Process management ,Scope (project management) ,Computer science ,business.industry ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Management Science and Operations Research ,General Business, Management and Accounting ,Industrial and Manufacturing Engineering ,Technology management ,ComputingMethodologies_PATTERNRECOGNITION ,Pricing strategies ,Manufacturing ,Marketing ,Unit cost ,business ,Duopoly ,Optimal decision - Abstract
Service-Oriented Manufacturing (SOM) strategy is a new manufacturing mode by integrating servitization with the traditional manufacturing industry. The advantages and importance of the SOM strategy are gradually recognized by more and more enterprises. However, the enterprises' specific cost structures and cost configurations for providing customized services have influences on the decisions about whether the SOM strategy should be adopted, how to determine the suitable scope of SOM, and how to set the suitable pricing scheme of their offerings. This paper performs an analytical study on the above objectives and proposes an optimal decision model for designing SOM strategy. Our analysis on the SOM strategy under competition offers some insights into: when enterprises should perform SOM; what the suitable scope of SOM is, and how to design pricing strategies for SOM. From this analytical study, we draw some managerial implications that: for an enterprise in a duopoly market, if the fixed part in the unit cost of service is lower than the one third of the equilibrium price, the enterprise should adopt the SOM strategy; in addition, one half of the enterprise's customers should be covered by the SOM strategy at most.
- Published
- 2012
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