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Aiming at the correlation among redundant components in optimization of system reliability redundancy, this paper makes use of Gumbel Copula function to describe this correlation and then the redundancy optimization model is improved. To solve the improved model, this paper uses the GAG1 heuristic algorithm. The sensitivity factor of this algorithm is corrected according to Gumbel Copula function. Finally, the numerical example indicates the feasibility, validity and practicality of this method. [ABSTRACT FROM AUTHOR]

With the aggravation of traffic jam traditional logistics network has reached high-point in big cities in China, so the logistics system on the ground will gradually transfer to underground on various layers in the future so as to release the ground space in cities. Based on SMT theory, this paper establishes underground tree logistics network layout model. Because SMT is NP-complete problem, the algorithm optimization capability is the key of research. Plant growth simulation algorithm (PGSA) in this paper is an intelligence optimization algorithm, which takes plant phototropism growth pattern as its heuristic criterion. Through artificial plant growth process in solution space of given logistics node set, we can get the optimal layout of underground logistics network in cities. Through the calculation of STEINLIB lab data announced internationally, PGSA is demonstrated with better accuracy, stability and global searching ability, by comparing the solutions of ant algorithm and simulated annealing algorithm. [ABSTRACT FROM AUTHOR]

The robustness of project schedule plays an important role for the smooth execution of project under uncertain conditions. The authors studied the resource-constrained project robust scheduling problem with random duration of activities. The objective was to arrange the start time of activities so as to maximize the robustness of project schedule under the constraints of renewable resources and project duration. The studied problem was identified and illustrated by using an example at first. Then the optimization model was constructed and three heuristic algorithms, including tabu search, multiple iteration, and random generation, were developed. Ultimately, the algorithms were tested on a standard instance set generated randomly. The influences of activity number, project duration, and resource strength on the algorithms' performance were analyzed. An instance was utilized to illustrate the research in the paper and the following conclusions were drawn: The solution quality of the tabu search is remarkably higher than that of the other two algorithms; as the resource strength or the project duration increase, the average value of objective function climbs and the quality advantage of the desirable solution of the tabu search augments. The research in this paper can provide decision supports for the preparation of project schedule under uncertain conditions. [ABSTRACT FROM AUTHOR]

One of the most important objectives of operations optimization in container terminal is to reduce the reshuffle ratio, whose important way is reshuffle optimization during picking up import containers. Based on analyzing the actual reshuffles of import containers in container yard, a simulation model of reshuffle process is proposed with Petri-net. Using simulation, the paper analyzes the correlation probability of reshuffles and its factors. Then a relocation probability estimate method is suggested with the main influencing factors. A total least-reshuffle-estimate rule based heuristic algorithm for reshuffle optimization of import containers. Simulation experiments results show that the accuracy of proposed algorithm can be 15% times more than OH and IH algorithm while solving larger-scale problems. [ABSTRACT FROM AUTHOR]

The paper presents a novel hybrid flow shop problem with multi-jobs families and no-buffer, and it is derived from hybrid operation of container terminal. Since the problem has these characteristics such as multi-jobs families, no-buffer, dedicated machines, setup time and operating time dependent on machines and sequence, we construct a new mixed integer linear programming model. As for the NP-hard of the problem, a constructive heuristic algorithm is developed to solve it. In the algorithm, a scheduling list consisting of triple machine matching pairs is dynamically produced based on machine's inventory and quota, and the triple machine matching pair corresponding to a job denotes the route or trip of a job in hybrid flow shop with 3 stages. Further, the performance of the algorithm is evaluated and validated through simulation experiments and analysis of lower bound, and can achieve approximate optimal solution with low computing cost. Especially, the algorithm is very effective for big size problems in practice. [ABSTRACT FROM AUTHOR]

There are many kinds of defects occurred in production plant, and those defects have different effects on the performance of production plant. So many kinds of inspection activities, or maintenance types such as daily inspection, weekly inspection, monthly inspection, yearly maintenance, and overhaul as well, are simultaneously applied on a production plant. The current research about inspection modeling pays more attention on the calculation of inspection cycle which is only for one maintenance type, not on the modeling of multiple nested inspection cycle. This has caused the serious problems of either over maintenance or insufficient maintenance. In this paper, all kinds of inspection activities are firstly given, and the relationship between different maintenance types is described. Secondly, a model of optimization grouping maintenance type at different inspection cycles for production plant is established. Based on the delay time maintenance theory, the key two terms, namely the expected failures number occurred in inspection cycle T and the expected defects number identified in inspection activities, are calculated. Thirdly, a new heuristic algorithm is proposed for solving the established model. As the proposed algorithm is very simple and easy to use, so it is better than branch-and-bound procedure to solve the nonlinear target function of integer variables. Finally, a case study is given to demonstrate the modeling and solution processes. [ABSTRACT FROM AUTHOR]

Traditional airline fleet planning methods could not reflect the robustness of fleet composition. In order to solve this shortcoming for airlines which operated in single-base linear route structure operating mode, this paper regarded minimum aircraft types deployed on single-base airport as objective, with flight pairing fleet assignment cost constraint, flight pairing fleet assignment uniqueness constraint, and least numbers of selected aircraft types constraint, to incorporate robustness into airline fleet planning model. Combining with only one competitive aircraft type in a desired fleet composition, the simulated annealing algorithm was employed to design heuristic algorithm for this proposed model. An empirical example containing 39 flight parings and 6 candidate aircraft types indicates that the fleet composition derived from traditional fleet planning method has three aircraft types while the proposed algorithm has only two. Furthermore, the fleet composition can well adapt to the market fluctuations, so the algorithm is feasible. [ABSTRACT FROM AUTHOR]

Accompanying repair is an important maintenance support form; optimally scheduling maintenance task will improve the efficiency for accompanying repair, and increase the combat efficiency for combat unit. In the paper, maintenance task scheduling heuristics in accompanying repair were researched with discrete event simulation methods. First, accompanying repair and maintenance task scheduling heuristics were presented. Next, simulation model of accompanying repair for equipment minimal combat unit was established. At last, maintenance task scheduling heuristics were evaluated, and influential factors, such as MTBF (mean time between fault), mission duration, preemption, priority updating methods, were analyzed through the simulation model. The simulation results show that it is better to prioritize the important maintenance task and allow preemption; when maintenance task emerging rate is high "MFCFS (modified first come first serve)" is better; when maintenance task emerging rate is low the "MSMPT (modified shortest mean process time)" is better; and it is reliable of "MEETOC (modified estimated earliest time to complete)". [ABSTRACT FROM AUTHOR]

This paper considers a problem of uniform-machine scheduling with machine release times to minimize makespan. Firstly, four properties of swapping jobs are proposed. Then, based on the properties, a heuristic algorithm is presented, which takes the LPT schedule as its initial solution and improves the solution by repeatedly swapping the jobs between two machines with the maximal and minimal makespan. Finally, computational results show that the presented heuristic is efficient and effective. [ABSTRACT FROM AUTHOR]

Vehicle routing problem (VRP) plays a vital role in logistics research. The multi-depot vehicle routing problem with time windows (MDVRPTW), an extension of VRP with time windows (VRPTW), is very complicated to be solved. This paper presented a two-stage heuristic to solve MDVRPTW. In the two-stage heuristic, aggregation-based clustering algorithm was firstly proposed to transfer MDVRPTW to several VRPTWs, and ant colony optimization (ACO) was developed to optimize each VRPTW. Two improvement strategies: crossover operation and adaptive ant-weight strategy, are designed to improve ACO. The performance of the two-stage heuristic was examined by use of some classic instances. Results show that the two-stage heuristic is a powerful tool for MDVRPTW. [ABSTRACT FROM AUTHOR]

In order to derive optimal lateral transshipment policy among retailers in supply chain system under stochastic demand environment, this paper developed a stochastic programming method to model the multilocation lateral transshipment problem in supply chain system. We considered a supply chain system that includes a supplier and multi retailers; they all adopt order-up-to approach to control inventories. Retailers faced stochastic demand and shared their inventories among each other--a retailer would transship residual stocks to other retailers which faced residual demand after demand realized. Based on the traditional hypothetical conditions, we developed a mix 0-1 programming model under system total cost minimization objective. Because of the stochastic vectors in the model, we covert the model to a stochastic expected value programming model, designed a heuristic algorithm that combined stochastic quasi gradient algorithm (SQGA) with genetic algorithm (GA), and explained the solution procedure. Numerical examples showed the efficiency of the model and algorithm. Besides, we investigated the case of coefficient demand and the case of violation of traditional transshipment conditions. Numerical results show that this model and algorithm is considerably effective in determining the optimal order-up-to points in supply chain system with retailers' lateral transshipment existence. [ABSTRACT FROM AUTHOR]

This paper deals with the human resource scheduling problem of multiple IT projects. According to its specific requirements on time and personnel, the duration of the whole development process can be divided into equal-length time slices. Based on the relations among activities and personnel in a certain time slice, the search tree of personnel scheduling solutions can be constructed. By connecting all the search trees sequentially from all the time slices, the solution tree for the whole problem can be generated and all the solutions can be listed. Then, based on the average of advanced completion rate and the variance of advanced completion rate, the optimal solution can be found. By adding heuristic rules to this algorithm, the searching space can contract rapidly, and the searching efficiency can be enhanced greatly. In view of the particularities of this algorithm, it can be applied to many generalized resource scheduling problems that possess similar conditions with the problem described above. After applying this algorithm to a mock example, some regular patterns emerged, showing the potential that further heuristic rules can be extracted. [ABSTRACT FROM AUTHOR]

The anchoring psychology is one of unreasonable psychologies existing in the financial market, which has important influence on the traders' decision-makings and the prices of the financial products. Combining with the characteristics of the futures market, this paper establishes a mathematical model about the impact of the anchoring psychology on the traders' trading behaviors and the short-term futures market price. This model is set based on the insufficient-adjustment-heuristic model which generated by anchoring psychology, and the anchoring point is the initial information obtained by traders. The analysis shows that the existence of anchoring psychology will increase the trading volume of futures contracts, resulting in short-term futures prices deviate from the theoretical value under the rational conditions, so that the price discovery function of futures prices and the effectiveness of futures market be affected. [ABSTRACT FROM AUTHOR]