A guided tabu search for the heterogeneous vehicle routeing problem

Abstract

The aim of this paper is to present a new algorithmic methodology for the heterogeneous fixed fleet vehicle routeing problem (HFFVRP). HFFVRP consists of determining the minimum cost routes for a fleet of vehicles in order to satisfy the demand of the customer population. The fleet composition is fixed and consists of various types of vehicles that differ with respect to their maximum carrying load and variable cost per distance unit. Our proposed algorithm called guided tabu search (GTS) is based on tabu search controlled by a continuous guiding mechanism that modifies the objective function of the problem. The role of this guiding strategy is to diversify the conducted search and help it overcome local optima encountered. The GTS method was applied successfully on HFFVRP benchmark problems producing best-known and new best-known solutions in short computational times.

Appendices

Appendix A: Analytic solutions for the HFFVRP benchmark instances of Taillard (1999)

Table A1, A2, A3, A4, A5, A6, A7 and A8

Table a1 Problem 13

Table a2 Problem 14

Table a3 Problem 15

Table a4 Problem 16

Table a5 Problem 17

Table a6 Problem 18

Table a7 Problem 19

Table a8 Problem 20

Appendix B: Analytic solutions for the benchmark instances of Golden et al (1984) with the fleet configuration found by Gendreau et al (1999)

Table B1, B2, B3, B4, B5, B6, B7 and B8

Table b1 Problem 13

Table b2 Problem 14

Table b3 Problem 15

Table b4 Problem 16

Table b5 Problem 17

Table b6 Problem 18

Table b7 Problem 19

Table b8 Problem 20