An integrated modelling approach for the bicriterion vehicle routing and scheduling problem with environmental considerations

The consideration of pollution in routing decisions gives rise to a new routing framework where measures of the environmental implications are traded off with business performance measures. To address this type of routing decisions, we formulate and solve a bi-objective time, load and path-dependent vehicle routing problem with time windows (BTL-VRPTW). The proposed formulation incorporates a travel time model representing realistically time varying traffic conditions. A key feature of the problem under consideration is the need to address simultaneously routing and path finding decisions. To cope with the computational burden arising from this property of the problem we propose a network reduction approach. Computational tests on the effect of the network reduction approach on determining non-dominated solutions are reported. A generic solution framework is proposed to address the BTL-VRPTW. The proposed framework combines any technique that creates capacity-feasible routes with a routing and scheduling method that aims to convert the identified routes to problem solutions. We show that transforming a set of routes to BTL-VRPTW solutions is equivalent to solving a bi-objective time dependent shortest path problem on a specially structured graph. We propose a backward label setting technique to solve the emerging problem that takes advantage of the special structure of the graph. The proposed generic solution framework is implemented by integrating the routing and scheduling method into an Ant Colony System algorithm. The accuracy of the proposed algorithm was assessed on the basis of its capability to determine minimum travel time and fuel consumption solutions. Although the computational results are encouraging, there is ample room for future research in algorithmic advances on addressing the proposed problem.     

Exact and meta-heuristic approach for a general heterogeneous dial-a-ride problem with multiple depots

Dial-a-ride problems are concerned with the design of efficient vehicle routes for transporting individual persons from specific origin to specific destination locations. In real-life this operational planning problem is often complicated by several factors. Users may have special requirements (e.g. to be transported in a wheelchair) while service providers operate a heterogeneous fleet of vehicles from multiple depots in their service area. In this paper, a general dial-a-ride problem in which these three real-life aspects may simultaneously be taken into account is introduced: the Multi-Depot Heterogeneous Dial-A-Ride Problem (MD-H-DARP). Both a three- and two-index formulation are discussed. A branch-and-cut algorithm for the standard dial-a-ride problem is adapted to exactly solve small problem instances of the MD-H-DARP. To be able to solve larger problem instances, a new deterministic annealing meta-heuristic is proposed. Extensive numerical experiments are presented on different sets of benchmark instances for the homogeneous and the heterogeneous single depot dial-a-ride problem. Instances for the MD-H-DARP are introduced as well. The branch-and-cut algorithm provides considerably better results than an existing algorithm which uses a less compact formulation. All seven previously unsolved benchmark instances for the heterogeneous dial-a-ride problem could be solved to optimality within a matter of seconds. While computation times of the exact algorithm increase drastically with problem size, the proposed meta-heuristic algorithm provides near-optimal solutions within limited computation time for all instances. Several best known solutions for unsolved instances are improved and the algorithm clearly outperforms current state-of-the-art heuristics for the homogeneous and heterogeneous dial-a-ride problem, both in terms of solution quality and computation time.     

时变交通下生鲜配送电动车辆路径优化方法

依据时变交通路网特点设计基于路段划分策略的行驶时间计算方法,综合考虑客户对生鲜产品最低新鲜度约束,车载限制和电动车电量约束,设计三约束决策因子方法.以配送总成本最小为目标,构建时变交通下电动车城市生鲜配送路径优化模型,根据模型特点设计自适应改进的蚁群算法.实验结果表明,本文方法能够根据客户生鲜新鲜度要求,客户属性和路网特性,合理安排发车时间,科学规划配送路径,有效避免交通拥堵;通过算法对比,本文模型和算法能够明显降低配送成本,提高企业经济效益.     

A two-phase tabu search approach to scheduling optimization in container terminals

An optimization model for scheduling of quay cranes （QCs） and yard trailers was proposed to improve the overall efficiency of container terminals. To implement this model, a two-phase tabu search algorithm was designed. In the QCs scheduling phase of the algorithm, a search was performed to determine a good QC unloading operation order. For each QC unloading operation order generated during the QC＇s scheduling phase, another search was run to obtain a good yard trailer routing for the given QC＇s unloading order. Using this information, the time required for the operation was estimated, then the time of return to availability of the units was fed back to the QC scheduler. Numerical tests show that the two-phase Tabu Search algorithm searches the solution space efficiently, decreases the empty distance yard trailers must travel, decreases the number of trailers needed, and thereby reduces time and costs and improves the integration and reliability of container terminal operation systems.     

基于电子海图的船舶定线辅助系统软件的实现

以船舶定线研究为目的，开发基于电子海图的交通数据处理与分析的软件，实现海上交通调查数据的计算机处理、交通流模式分析及定线技术的应用。     

长江航路的改革与发展

航路改革是长江航运史上的一次革命,它规范了船舶航行秩序,大大降低了交通事故发生率,提高了通航效率。本文从航路改革的意义,作法,收益入手,重点对航路改革的发展进行了探讨,具有一定的实践指导意义。     

Modeling techniques for periodic vehicle routing problems

This paper presents a continuous approximation model for the period vehicle routing problem with service choice (PVRP-SC). The PVRP-SC is a variant of the period vehicle routing problem in which the visit frequency to nodes is a decision of the model. This variation can result in more efficient vehicle tours and/or greater service benefit to customers. We present a continuous approximation model to facilitate strategic and tactical planning of periodic distribution systems and evaluate the value of service choice. Further, results from the continuous model can provide guidelines for constructing solutions to the discrete PVRP-SC.     

A Hybrid TCNN Optimization Approach for the Capacity Vehicle Routing Problem

Introduction The vehicle routing problem(VRP)is one ofthe well-known NP-hard optimization problems[1]occurring in many transport logistics and distribu-tion systems of considerable economic significance.The capacity vehicle routing problem(CVRP)likeVRP with the additional constraint that every vehi-cle must have a capacity,so it is also an NP-hardoptimization problems.It involves minimizing costvehicle schedules for a fleet of vehicles originatingand terminating from a central depot.The …     

Matlab在航线配船中的应用

利用OLE自动化技术实现Visual Basic调用Matlab函数进行航线配船,应用于赤水河机动驳船队配船,证明该方法的有效性,将Visual Basic的可视化界面与Matlab强大的数值计算相结合,为航线配船提供了一种有效的解决手段。     

不固定牵引方式双肩回交路机车最优配置的遗传算法

机车周转图的编制是多约束条件的组合优化问题。针对不固定牵引方式双肩回交路机车周转图编制建立数学模型,并以机车在2个折返段(站)和基本段(站)总停留时间最少为目标,设计不固定牵引方式双肩回交路机车运转制下求解机车最优配置的遗传算法。基于知识的变异方法和采用交叉概率、变异概率随个体优劣程度自适应的调整策略,提高算法的局部搜索能力以及收敛和优化性能。以某实际列车运行图为例进行仿真计算,结果表明:运用该算法可使机车的段内总停留时间和需要的牵引机车台数较实际的机车周转图分别减少约21%和8.6%。