Tabu search for a multi-objective routing problem

Abstract

Multi-objective optimization problems deal with the presence of different conflicting objectives. Given that it is not possible to obtain a single solution by optimizing all the objectives simultaneously, a common way to face these problems is to obtain a set of efficient solutions called the non-dominated frontier. In this paper we address the problem of routing school buses with two objectives: minimize the number of buses, and minimize the longest time a student would have to stay in the bus. The tradeoff in this problem is between service level, which is represented by the maximum route length, and operational cost, which is represented by the number of buses in the solution. We present different constructive solution methods and a tabu search procedure to obtain non-dominated solutions. The procedure is coupled with an intensification phase based on the path relinking methodology; a strategy proposed several years ago, which has been rarely used in actual implementations. Computational experiments with real data in the context of routing school buses in a rural area, establish the effectiveness of our procedure in relation to the approach previously identified to be best.

Multi-objective vehicle routing problems

“…Both Corberan et al [11] and Pacheco and Marti [51] examined methods for transporting students from home to school, and back again. The transportation had to be accomplished as safely as possible, while still considering economics and comfort.…”

“…Although cost minimization is the most common objective, this objective is sometimes ignored, as is the case in the studies by Corberan et al [11] and Pacheco and Marti [51]. These authors chose instead to minimize the makespan (i.e., to minimize the length of the longest tour).…”

“…One objective that often appears is the minimization of the number of vehicles, which can be interpreted economically, in that fewer vehicles means less monetary investment (e.g., for vehicle purchases, gas, and/or drivers' salaries) [11,19,[48][49][50][51]64,66].…”

A heuristic two‐phase solution approach for the multi‐objective dial‐a‐ride problem

“…[25,26,31,35,38,39]. Very recently, a survey on multi-objective routing problems has been published by Jozefowiez et al [27].…”

A multi-stop routing problem

“…Heuristic procedures have been developed in the area of bus routing, specifically Corberán et al (2002) address the problem of routing school buses, also Pacheco and Martí (2006) develop a hybrid metaheuristic algorithm for multi-objective routing problems.…”