具有模糊预约时间的VRP混合遗传算法

在对具有模糊预约时间的多对多货物收发情况下的车辆路径问题进行简单描述的基础上,构建了该问题的多目标数学规划模型,提出了解决该问题的一种基于插入启发式算法、并用修正的推—碰—掷过程进行改进的混合遗传算法,最后,给出了该问题的一个计算实例,并与改进的Solomon插入启发式算法进行了比较.     

Multi-depot vehicle routing problem with time windows under shared depot resources

A new variant of multi-depot vehicle routing problem with time windows is studied. In the new variant, the depot where the vehicle ends is flexible, namely, it is not entirely the same as the depot that it starts from. An integer programming model is formulated with the minimum total traveling cost under the constrains of time window, capacity and route duration of the vehicle, the fleet size and the number of parking spaces of each depot. As the problem is an NP-Hard problem, a hybrid genetic algorithm with adaptive local search is proposed to solve it. Finally, the computational results show that the proposed method is competitive in terms of solution quality. Compared with the classic MDVRPTW, allowing flexible choice of the stop depot can further reduce total traveling cost.     

有模糊时间窗的车辆调度组合干扰管理研究

研究带有模糊时间窗的车辆调度组合干扰管理模型及其混合遗传算法.采用时间窗模糊化处理方法,定义客户满意度函数,根据干扰管理思想对车辆调度中组合性干扰事件进行分析,从配送路径、配送成本和客户满意度三个方面进行干扰辨识与度量,建立基于模糊时间窗的车辆调度组合干扰管理模型;构造模型求解的混合遗传算法,将最佳客户插入规则与遗传算法结合,同时在算法中嵌入模糊优化程序以处理问题的模糊特征;进行数值实验,实验结果验证了模型与算法的有效性.     

A heuristic algorithm for the period vehicle routing problem

In this paper we consider the period vehicle routing problem, which is the problem of designing routes for delivery vehicles to meet customer service level requirements (not all customers require delivery on every day in the period). A heuristic algorithm, based upon the daily vehicle routing algorithm of Fisher and Jaikumar, is presented and computational results are given for test problems drawn from the literature.     

An investigation into a new class of vehicle routing problem with backhauls

A new version of the vehicle routing problem with backhauls is presented. In this new problem backhauls are not restricted to be visited once all linehaul customers have been served, neither are backhaul customers fully mixed with linehaul customers. In this problem the user based on his or her experience, the vehicle capacity, the type of products and the type of vehicle used, can define the position along a route from which the first backhaul customer may be visited. An insertion-type heuristic is put forward for this class of problems. An analysis of the improvement in route cost obtained by allowing a relaxation in the restriction of the mix of linehaul and backhaul customers is reported.     

竞争决策算法及其在车辆路径问题中的应用

在分析自然界各种竞争机制和人类社会决策原理的基础上,利用竞争造就优化和决策左右结果的特性,提出了一种能广泛应用于组合优化难题的新型算法———竞争决策算法(CDA),并给出了CDA的通用模型.车辆路径问题(VRP)是一个著名的NP难题,也是物流领域内一个重要的调度问题,利用CDA的通用模型设计了一个针对VRP的快速求解算法,并用该算法求解了VRP标准测试库中的实例,经过大量数据测试和验证,获得了令人满意的效果,其中部分问题的解优于目前公布的最好解.     

动态车辆路径问题排队模型分析

分析了一类动态车辆路径问题,其中顾客需求以泊松流形式出现,现场服务时间服从一般分布.提出解决该问题的两种策略:顺序服务策略和中点改进策略,利用排队论、几何概率论等领域的知识分别求出了这两种策略的系统时间,并通过仿真数据实验验证了这两种策略的有效性.     

环状区域的车辆路径方案生成系统及优化模型

针对顾客满足环状区域分布的车辆路径问题(VRP),以大幅度地缩减问题求解的状态空间为突破口,引入人工智能和运筹学理论,提出求解这类特殊车辆路径问题的两阶段方法.第1阶段考虑行车时间和车载容量,提出带有控制策略的深度优先搜索算法自动生成备选的车辆路径方案集合.第2阶段将此备选方案集合归结为整数规划模型.采用VB6.0编程语言构建了车辆路径方案生成系统,并实现该系统与运筹学求解软件lindo的集成.通过案例验证了上述方法及自动求解系统的有效性.该项研究为解决环状配送区域的车辆路径问题这一难题提供了新方法.     

An investigation into the vehicle routing problem with time windows and link capacity constraints

In this work, we investigate a new, yet practical, variant of the vehicle routing problem called the vehicle routing problem with time windows and link capacity constraints (VRPTWLC). The problem considers new constraints imposed on road links with regard to vehicle passing tonnage, which is motivated by a business project with a Hong Kong transportation company that transports hazardous materials (hazmats) across the city and between Hong Kong and mainland China. In order to solve this computationally challenging problem, we develop a tabu search heuristic with an adaptive penalty mechanism (TSAP) to help manage the company's vehicle fleet. A new data set and its generation scheme are also presented to help validate our solutions. Extensive computational experiments are conducted, showing the effectiveness of the proposed solution approach.     

A lower bound for the adaptive two-echelon capacitated vehicle routing problem

Adaptive two-echelon capacitated vehicle routing problem (A2E-CVRP) proposed in this paper is a variant of the classical 2E-CVRP. Comparing to 2E-CVRP, A2E-CVRP has multiple depots and allows the vehicles to serve customers directly from the depots. Hence, it has more efficient solution and adapt to real-world environment. This paper gives a mathematical formulation for A2E-CVRP and derives a lower bound for it. The lower bound is used for deriving an upper bound subsequently, which is also an approximate solution of A2E-CVRP. Computational results on benchmark instances show that the A2E-CVRP outperforms the classical 2E-CVRP in the costs of routes.     

A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority

In this paper, a multi-objective vehicle routing and scheduling problem with uncertainty in priority and request of customers is presented. In the proposed model, a set of dynamic requests is received over time, and the planner does not have any information regarding their location and size until they arrive. Moreover, the routing model aims to satisfy different customers according to their specific time windows which were predefined by an expert as (being very important, important, casual or unimportant). This paper uses the proposed model as a multi-objective problem where the total required number of vehicles, the total distance travelled and the waiting time imposed on vehicles are minimized, and the total customers’ satisfaction for service is maximized. An efficient framework for solving this model is designed and its performance is evaluated in different steps for various test problems generalized from Solomon’s VRPTW benchmark problems. The various heuristics and improvement concepts incorporate local exploitation in the evolutionary search, and the concept of Pareto optimality for the multi-objective optimization is used in the proposed procedure. The computational experiments on data sets illustrate the efficiency and effectiveness of the proposed approach.     

A reactive tabu search algorithm for the vehicle routing problem with simultaneous pickups and deliveries

The vehicle routing problem with pickups and deliveries (VRPPD) extends the vehicle routing problem (VRP) by allowing customers to both send and receive goods. The main difficulty of the problem is that the load of vehicles is fluctuating rather than decreasing as in the VRP. We design a reactive tabu search metaheuristic that can check feasibility of proposed moves quickly and reacts to repetitions to guide the search. Several new best solutions are found for benchmark problems.     

Self-organizing maps in population based metaheuristic to the dynamic vehicle routing problem

We consider the dynamic vehicle routing problem (dynamic VRP). In this problem, new customer demands are received along the day. Hence, they must be serviced at their locations by a set of vehicles in real time. The approach to address the problem is a hybrid method which manipulates the self-organizing map (SOM) neural network into a population based evolutionary algorithm. The method, called memetic SOM, illustrates how the concept of intermediate structure, also called elastic net or adaptive mesh concept, provided by the original SOM can naturally be applied into a dynamic setting. The experiments show that the heuristic outperforms the approaches that were applied to the Kilby et al. 22 problems with up to 385 customers. It performs better with respect to solution quality than the ant colony algorithm MACS-VRPTW, a genetic algorithm, and a multi-agent oriented approach, with a computation time used roughly 100 times lesser.     

An exponential (matching based) neighborhood for the vehicle routing problem

We introduce an exponential neighborhood for the Vehicle Routing Problem (vrp) with unit customers’ demands, and we show that it can be explored efficiently in polynomial time by reducing its exploration to a particular case of the Restricted Complete Matching (rcm) problem that we prove to be polynomial time solvable using flow techniques. Furthermore, we show that in the general case with non-unit customers’ demands the exploration of the neighborhood becomes an -hard problem.     

大规模邻域搜索算法求解时变车辆调度问题

对时变网络车辆调度问题提出一种满足先入先出准则的时变处理方法,并建立相应的数学模型,提出一种基于大规模邻域搜索技术的智能优化算法进行求解,算法顶层采用动态规划算法搜索环状交换邻域以得到每辆车的最佳服务顾客集合;底层设计动态搜索算法用以安排每辆车的最佳服务路线.在此基础上提出顶层加入虚拟顾客和底层嵌入insert两类改进策略.通过实验仿真比较,验证了所提算法的有效性.     

The facility location problem with Bernoulli demands

This paper presents the facility location problem with Bernoulli demands. In this capacitated discrete location stochastic problem the goal is to define an a priori solution for the locations of the facilities and for the allocation of customers to the operating facilities that minimizes the sum of the fixed costs of the open facilities plus the expected value of the recourse function. The problem is formulated as a two-stage stochastic program and two different recourse actions are considered. For each of them, a closed form is presented for the recourse function and a deterministic equivalent formulation is obtained for the case in which the probability of demand is the same for all customers. Numerical results from computational experiments are presented and analyzed.     

带货物权重的车辆路径问题及遗传算法

考虑一个分销中心、多个零售商组成的分销网络系统中具有柔性车辆能力的带货物权重的车辆路径问题.并根据车辆的满载情况采用了不同的运输策略,即单点运输和多点运输方式.在多点运输方式下,与以往诸多研究不同的是,文章建立了一种基于货物权重的VRP模型——WVRP,即在安排车辆线路时每个零售商的货物需求量也作为一个因素考虑,尽可能使车辆优先供货需求量较大的零售商.最后,针对问题的性质,开发了一种基于划分的遗传算法PB-GA对问题进行求解,并与一般遗传算法及常用的启发式算法进行了分析比较.     

Two approaches to solving the multi-depot vehicle routing problem with time windows in a time-based logistics environment

This paper presents a two-phase heuristic method that can be used to efficiently solve the intractable multi-depot vehicle routing problem with time windows. The waiting time that was ignored by previous researchers is considered in this study. The necessity of this consideration is verified through an initial experiment. The results indicate that the waiting time has a significant impact on the total distribution time and the number of vehicles used when solving test problems with narrow time windows. In addition, to fairly evaluate the performance of the proposed heuristic method, a meta-heuristic method, which extends the unified tabu search of Cordeau et al., is proposed. The results of a second experiment reveal that the proposed heuristic method can obtain a better solution in the case of narrow time windows and a low capacity ratio, while the proposed meta-heuristic method outperforms the proposed heuristic method, provided that wide time windows and a high capacity ratio are assumed. Finally, a well-known logistics company in Taiwan is used to demonstrate the method, and a comparison is made, which shows that the proposed heuristic method is superior to the current method adopted by the case company.     

A multi-compartment vehicle routing problem arising in the collection of olive oil in Tunisia

We introduce, model and solve to optimality a rich multi-product, multi-period and multi-compartment vehicle routing problem with a required compartment cleaning activity. This real-life application arises in the olive oil collection process in Tunisia, where regional collection offices dispose of a fleet of vehicles to collect one or several grades of olive oil from a set of producers. For each grade, the quantity offered by a producer changes dynamically over the planning horizon. We first provide a mathematical formulation of the problem, along with a set of known and new valid inequalities. We then propose an exact branch-and-cut algorithm to solve the problem. We evaluate the performance of the algorithm on real data sets under different transportation scenarios to demonstrate to our industrial partner the advantages of using multi-compartment vehicles.     

Distance constrained vehicle routing problem to minimize the total cost: algorithms and complexity

Journal of Combinatorial Optimization - Given $$\lambda >0$$ , an undirected complete graph $$G=(V,E)$$ with nonnegative edge-weight function obeying the triangle inequality and a depot...