Bi-Objective Bus Routing: An Application to School Buses in Rural Areas

The min-max vehicle routing problem (VRP) is a variant of the classical VRP in which the objective is to minimize the duration of the longest route. Examination of the VRP literature indicates that the min-max VRP has received less attention than other variants have over the years. However, the prob...

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Bibliographic Details
Published in:Transportation science 2013-08, Vol.47 (3), p.397-411
Main Authors: Pacheco, Joaquín, Caballero, Rafael, Laguna, Manuel, Molina, Julián
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Assignment problem
bi-objective optimization
Bus travel
Cost control
Experimental methods
Genetic algorithms
Hazardous materials
Heuristic
Management science
Mathematical optimization
metaheuristics
Optimization
Problem solving
Road transport
Route optimization
routing
Rural areas
School buses
School districts
Studies
Transport
Vehicles
Western Europe
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Summary:The min-max vehicle routing problem (VRP) is a variant of the classical VRP in which the objective is to minimize the duration of the longest route. Examination of the VRP literature indicates that the min-max VRP has received less attention than other variants have over the years. However, the problem has important practical applications, such as those related to routing school buses. In this setting, in addition to the min-max criterion imposed on the time it takes to complete the longest route, school districts are concerned with the minimization of the total distance traveled, which is the objective of the classical VRP. Hence, the problem is formulated as a bi-objective optimization model that trades off service (i.e., the minimization of the longest route) and operational cost (i.e., the minimization of the total distance traveled). We develop a solution procedure for this problem by applying tabu search within the framework of Multiobjective Adaptive Memory Programming and compare it to an implementation of the Non-dominated Sorting Genetic Algorithm-a well-known approach to multiobjective optimization. We also assess the merit of the solution method by comparing our approximations with solution frontiers obtained with an -constraint implementation.
ISSN:0041-1655
1526-5447
DOI:10.1287/trsc.1120.0437