Synchronized Planning of Interdependent Resources in Transport Logistics

基于自己以前的工作，计划项目的目标是有助于研究领域的建模和精确和启发式求解的车辆路径问题（VRPMSs）。在车辆路径的基本问题，一组运输请求。运输请求包括将一定数量的货物交付给指定的客户（位置）。为此，提供了一套装载能力有限的车辆。该问题是确定一个成本最小的路径规划，即将运输请求分组到每个可以由一辆车执行的集群中，并设置每个集群中的请求的顺序，使得总的行驶距离或所需车辆的数量最小化。VRPMS与其他VRP的不同之处在于，可用于满足运输请求的资源，即车辆，司机和集装箱，是相互依赖的，并且它们的使用必须在几个方面同步：除了决定哪些资源应该执行哪些请求的要求之外，VRPMS还具有关于时间、空间和负载的同步要求。这种持续研究活动的一个原因是VRP带来的数学和信息挑战。另一个原因是车辆路线安排具有相当大的实际意义。然而，到目前为止，VRPMSs在很大程度上被科学所忽视。这主要是由于这样一个事实，即仅仅同步的请求履行不会引起资源之间的相互依赖性，而多个同步要求导致复杂的相互依赖性，这是不容易处理的算法。VRPMS的应用可以在食品配送，家庭护理人员调度和多式联运在小于卡车的业务，包裹递送服务，和城市物流。一方面采用离散优化的精确方法，另一方面采用遗传算法和元遗传算法。后者不能保证找到最优解，但它们被使用，因为现实世界规模的问题实例仍然不能在合理的时间内一致地精确解决。因此，计划项目的交付是：-一般VRPMS的通用启发式算法的实现-一般VRPMS的精确算法的实现-关于解决不同类型VRPMS的解决方案程序性能的理论，数学证明和经验，统计验证声明

Based on own previous work, the objective of the planned project is to contribute to research in the field of modelling and exact and heuristic solution of vehicle routing problems with multiple synchronization constraints (VRPMSs).In the basic problem of vehicle routing, a set of transport requests is given. A transport request consists in delivering a certain amount of a good to a specified customer (location). To this end, a set of vehicles with limited loading capacity is available. The problem is to determine a cost-minimal routing plan, that is, to group transport requests into clusters that can be performed by one vehicle each, and to set the sequence of the requests in each cluster, so that the overall travelled distance or the number of necessary vehicles is minimized.VRPMSs differ from other VRPs in that the resources available to fulfil the transport requests, that is, vehicles, drivers and containers, are interdependent, and that their use must be synchronized in several respects: Beside the requirement to decide which resource(s) should perform which request(s), VRPMSs possess synchronization requirements with regard to time, space, and load.VRPs have been scientifically studied for years. One reason for this continued research activity is the mathematical and informational challenge that VRPs pose. Another reason is the considerable practical relevance of vehicle routing. VRPMSs, however, have been largely neglected by science so far. This is mostly due to the fact that a mere synchronization of request fulfilment does not induce interdependencies between resources, whereas multiple synchronization requirements lead to intricate interdependencies that are not easy to handle algorithmically.Applications of VRPMSs can be found in food distribution, home care staff dispatching and multi-modal transport in the less-than-truckload business, parcel delivery services, and city logistics.For solving VRPs, on the one hand, exact methods of discrete optimization are used, on the other hand, heuristics and metaheuristics are applied. The latter do not guarantee finding optimal solutions, but they are used, because problem instances of real-world size can still not be consistently solved exactly in reasonable time. Therefore, the deliveries of the planned project are:- An implementation of a generic heuristic for general VRPMSs- An implementation of an exact algorithm for general VRPMSs- Theoretical, mathematically proven and empirical, statistically validated statements on the performance of the solution procedures for solving different types of VRPMSs