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Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In densely populated areas, ridepooling services are becoming more and more popular and can contribute to promote sustainable mobility concepts. In this paper, we study a dynamic dial-a-ride problem and propose a novel two-phase multiple plan approach. By maintaining multiple plans simultaneously over the course of the optimization procedure, we increase the likelihood and speed of a successful insertion for dynamically arising customer requests. Additionally, we present a new metric to replace the commonly used distance minimization as guidance within the optimization procedure. In order to examine the impact of certain instance characteristics on the quality of the solutions, we evaluate our design decisions on various instance sets. The results show that the proposed method consistently outperforms commonly used single plan approaches. [ABSTRACT FROM AUTHOR]

Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper describes a long-term scheduling problem for thermal power plants and energy storages. In addition, renewable energy sources are integrated by considering the residual demand. Besides the classical minimization of the production costs, emission-related costs are taken into account. Thereby, emission costs are determined by market prices for CO 2 emission certificates (i.e., using the EU emissions trading system). For the proposed unit commitment problem with hydrothermal coordination for economic and emission control, an enhanced mixed-integer linear programming model is presented. Moreover, a new heuristic approach is developed, which consists of two solution stages. The heuristic first performs an isolated dispatching of thermal plants. Then, a re-optimization stage is included in order to embed activities of energy storages into the final solution schedule. The considered approach is able to find outstanding schedules for benchmark instances with a planning horizon of up to one year. Furthermore, promising results are also obtained for large-scale real-world electricity systems. For the German electricity market, the relationship of CO 2 certificate prices and the optimal thermal dispatch is illustrated by a comprehensive sensitivity analysis. [ABSTRACT FROM AUTHOR]

In this paper, we consider a long-term unit commitment problem with thermal and renewable energy sources, where system operating costs have to be minimized. The problem is enhanced by adding pumped storages, where water is stored in reservoirs, being turbinated or pumped up if it is beneficial in terms of reducing the operating costs. We present a tight mixed-integer linear programming model with a redefinition of decision variables and a reformulation of constraints, e.g., for the spinning reserve. The model serves as a basis for a new decomposition method, where fix-and-optimize schemes are used. In particular, a time-oriented, a unit-oriented, and a generic fix-and-optimize procedure are presented. A computational performance analysis shows that the mixed-integer linear model is efficient in supporting the solution process for small- and medium-scale instances. Furthermore, the fix-and-optimize procedures are able to tackle even large-scale instances. Particularly, problem instances with real-world energy demands, power plant-specific characteristics, and a one-year planning horizon with hourly time steps are solved to near-optimality in reasonable time. [ABSTRACT FROM AUTHOR]

In this paper, a scheduling problem that occurs in potash mining is introduced, where a block excavation sequence has to be found taking into account a limited number of underground machines as well as safety-related restrictions. The aim is to minimize the maximum completion time of excavations, i.e., the makespan. The resulting problem can be transformed into a hybrid flow shop scheduling problem with reentry, unrelated machines, and job-precedences. A mixed-integer linear model is presented and small-scale instances are solved with CPLEX. In order to tackle medium- and large-scale instances heuristically, a basic and an advanced multi-start algorithm are developed, based on a specific priority rule-based construction procedure. In addition, a modified version of the Giffler and Thompson procedure is applied. Computational experiments are conducted on problem instances derived from real-world data in order to evaluate the performances of the proposed solution procedures. [ABSTRACT FROM AUTHOR]

Resource leveling problems arise whenever it is expedient to reduce the fluctuations in resource utilization over time, while maintaining a prescribed project completion deadline. Several resource leveling objective functions may be defined, consideration of which results in well-balanced resource profiles. In this paper, we concentrate on a special objective function that determines the costs arising from increasing or decreasing the resource utilizations. The resulting total adjustment cost problem occurs, for example, in the construction industry and can be formulated using mixed-integer linear programming models. Apart from a discrete time-based formulation, two polynomial formulations, namely an event-based model and a start-based model, which exploit structural properties of the problem are presented. In addition, a heuristic solution algorithm is proposed to generate start solutions for the problem. We use CPLEX 12.4 to solve medium-scale instances known from the literature. A computational performance analysis shows that the discrete time-based model and the start-based model are suitable for practical applications. [ABSTRACT FROM AUTHOR]

This paper studies a simultaneous vehicle and crew routing and scheduling problem arising in long-distance road transport in Europe: Pickup-and-delivery requests have to be fulfilled over a multi-period planning horizon by a heterogeneous fleet of trucks and drivers. Typically, in the vehicle routing literature, a fixed assignment of a driver to a truck is assumed. In our approach, we abandon this assumption and allow truck/driver changes at geographically dispersed relay stations. This offers greater planning flexibility and allows a better utilization of trucks, but also creates intricate interdependencies between trucks and drivers and requires the synchronization of their routes. A solution heuristic based on a two-stage decomposition of the problem is developed, taking into account European Union social legislation for drivers, and computational experiments using real-world data provided by a major German forwarder are presented and analyzed. The obtained results suggest that for the vehicle and driver cost structure prevalent in Western Europe and for transport requests that are not systematically acquired to complement one another, no cost savings are possible through simultaneous vehicle and crew routing and scheduling, although no formal proof of this fact is possible. [ABSTRACT FROM AUTHOR]

In reverse logistics networks, products (e.g., bottles or containers) have to be transported from a depot to customer locations and, after use, from customer locations back to the depot. In order to operate economically beneficial, companies prefer a simultaneous delivery and pick-up service. The resulting Vehicle Routing Problem with Simultaneous Delivery and Pick-up (VRPSDP) is an operational problem, which has to be solved daily by many companies. We present two mixed-integer linear model formulations for the VRPSDP, namely a vehicle-flow and a commodity-flow model. In order to strengthen the models, domain-reducing preprocessing techniques, and effective cutting planes are outlined. Symmetric benchmark instances known from the literature as well as new asymmetric instances derived from real-world problems are solved to optimality using CPLEX 12.1. [ABSTRACT FROM AUTHOR]

In this paper we address a rich vehicle routing problem that arises in real-life applications. Among other aspects we consider time windows, simultaneous delivery and pick-up at customer locations and multiple use of vehicles. To guarantee a coordinated material flow at the depot, we include the timed allocation of vehicles to loading bays at which the loading and unloading activities can occur. The resulting vehicle routing problem is formulated as a two-index vehicle-flow model which integrates the routing under real-life conditions and the assignment of vehicles to loading bays at the depot. We use CPLEX 11.0 to solve medium-sized instances that are derived from the extended Solomon test set. The selective implementation of preprocessing techniques and cutting planes improves the solver performance significantly. [ABSTRACT FROM AUTHOR]

Copyright of Zeitschrift für Planung & Unternehmenssteuerung is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)