Thirty years of heterogeneous vehicle routing

It has been around thirty years since the heterogeneous vehicle routing problem was introduced, and significant progress has since been made on this problem and its variants. The aim of this survey paper is to classify and review the literature on heterogeneous vehicle routing problems. The paper also presents a comparative analysis of the metaheuristic algorithms that have been proposed for these problems

An Application of the Multi-Level Heuristic for the Heterogeneous Fleet Vehicle Routing Problem

The Multi-Level heuristic is used to investigate the heterogeneous fleet vehicle routing problem (HFVRP). The initial solution for the Multi-Level heuristic is obtained by Dijkstra\u27s algorithm based on a cost network constructed by the sweep algorithm and the 2-opt procedure. The proposed algorithm uses a number of local search operators such as swap, 1-0 insertion, 2-opt, and Dijkstra\u27s Algorithm. In addition, in order to improve the search process, a diversification procedure is applied. The proposed algorithm is thentested on the data sets from the literature

A robust solving strategy for the vehicle routing problem with multiple depots and multiple objectives

This document presents the development of a robust solving strategy for the Vehicle Routing Problem with Multiple Depots and Multiple Objectives (MO-MDVRP). The problem tackeled in this work is the problem to minimize the total cost and the load imbalance in vehicle routing plan for distribution of goods. This thesis presents a MILP mathematical model and a solution strategy based on a Hybrid Multi- Objective Scatter Search Algorithm. Several experiments using simulated instances were run proving that the proposed method is quite robust, this is shown in execution times (less than 4 minutes for an instance with 8 depots and 300 customers); also, the proposed method showed good results compared to the results found with the MILP model for small instances (up to 20 clients and 2 depots).MaestríaMagister en Ingeniería Industria

On green routing and scheduling problem

The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

Filo büyüklüğü ve karma araç rotalama problemleri i̇çin yeni bir yapısal rotalama algoritması

In this study, a new constructive routing algorithm for fleet size and mix vehicle routing problem is proposed in which residual costs rather than vehicle types are considered for route selection.The algorithm of the proposed routing approach is given and then the solution phases of a sample problem are shown by using the given algorithm. In order to highlight the performance of the routing approach, Golden’s 12 test problems (Fleet Size and Mix Vehicle Routing Problem with Fixed Cost) are used. It is seen that the proposed method has better average time complexity and cost performances than Ochi’s routing approach. Therefore, the solutions of the proposed method that uses vehicle type information are better than those of the methods that use residual cost based on the vehicle type information

A new heuristic routing algorithm for fleet size and mix vehicle routing problem

Ochi’s approach solves the heterogenous vehicle routing problem using the constraint having fixed costs as a multiplier of residuals. However, in this approach, there is not any information about which vehicle will be assigned to the route related to this constraint. In our study, Ochi’s approach is interpreted again in terms of vehicle capacity and number of customers assigned to each route. The proposed routing approach is taking the higher capacity vehicle for improving the performance. Then the solution phases of a sample problem are shown by using the given algorithm. In order to highlight the performance of the routing approach, Golden’s 12 test problems (Fleet Size and Mix Vehicle Routing Problem with Fixed Cost) are used. It is seen that the proposed method has better average time complexity and equal cost performances than Ochi’s routing approach. Therefore, the solutions with higher capacity vehicle of the proposed method that uses vehicle type information are better than those of the methods that use residual cost based on the vehicle type information

A group genetic algorithm for the fleet size and mix vehicle routing problem

In logistics management, the use of vehicles to distribute products from suppliers to customers is a major operational activity. Optimizing the routing of vehicles is crucial for providing cost-effective services to customers. This research addresses the fleet size and mix vehicle routing problem (FSMVRP), where the heterogeneous fleet and its size are to be determined. A group genetic algorithm (GGA) approach, with unique genetic operators, is designed and implemented on a number of existing benchmark problems. GGA demonstrates competitive performance in terms of cost and computation time when compared to other heuristics