article

A backtracking adaptive threshold accepting algorithm for the vehicle routing problem

Authors:

C. D. Tarantilis,

C. T. Kiranoudis,

V. S. VassiliadisAuthors Info & Claims

Systems Analysis Modelling Simulation, Volume 42, Issue 5

Pages 631 - 664

https://doi.org/10.1080/716067183

Published: 01 May 2002 Publication History

Abstract

The aim of this study is to describe a new stochastic search metaheuristic algorithm for solving the capacitated Vehicle Routing Problem, termed as the Backtracking Adaptive Threshold Accepting (BATA) algorithm. Our effort focuses on developing an innovative method, which produces reliable and high quality solutions in a reasonable amount of time, without requiring substantial parameter tuning. BATA belongs to the class of threshold accepting algorithms. Its main difference over a typical threshold-accepting algorithm is that during the optimization process, the value of the threshold not only is lowered but also raised, or backtracked, depending on the success of the inner loop iterations to provide an acceptable new configuration (set of routes) replacing the previous one. This adaptation of the value of the threshold, plays an important role in finding the high quality solutions demonstrated in computational results presented in this study.

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Cited By

Gokalp OUgur A(2020)A multi-start ILS–RVND algorithm with adaptive solution acceptance for the CVRPSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-04072-624:4(2941-2953)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00500-019-04072-6
Marinaki MMarinakis Y(2016)A Glowworm Swarm Optimization algorithm for the Vehicle Routing Problem with Stochastic DemandsExpert Systems with Applications: An International Journal10.1016/j.eswa.2015.10.01246:C(145-163)Online publication date: 15-Mar-2016
https://dl.acm.org/doi/10.1016/j.eswa.2015.10.012
Muñuzuri JDomíngueza IBerrocal MEscudero A(2016)An allocation-scheduling heuristic to manage train traffic in an intermodal terminalComputers in Industry10.1016/j.compind.2016.07.00682:C(196-204)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.compind.2016.07.006
Show More Cited By

Index Terms

A backtracking adaptive threshold accepting algorithm for the vehicle routing problem
1. Computing methodologies
  1. Artificial intelligence
    1. Search methodologies
      1. Heuristic function construction
2. Mathematics of computing
  1. Probability and statistics

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Published In

cover image Systems Analysis Modelling Simulation

Systems Analysis Modelling Simulation Volume 42, Issue 5

May 2002

158 pages

ISSN:0232-9298

Issue’s Table of Contents

Publisher

Gordon and Breach Science Publishers, Inc.

United States

Publication History

Published: 01 May 2002

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Cited By

Gokalp OUgur A(2020)A multi-start ILS–RVND algorithm with adaptive solution acceptance for the CVRPSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-019-04072-624:4(2941-2953)Online publication date: 1-Feb-2020
https://dl.acm.org/doi/10.1007/s00500-019-04072-6
Marinaki MMarinakis Y(2016)A Glowworm Swarm Optimization algorithm for the Vehicle Routing Problem with Stochastic DemandsExpert Systems with Applications: An International Journal10.1016/j.eswa.2015.10.01246:C(145-163)Online publication date: 15-Mar-2016
https://dl.acm.org/doi/10.1016/j.eswa.2015.10.012
Muñuzuri JDomíngueza IBerrocal MEscudero A(2016)An allocation-scheduling heuristic to manage train traffic in an intermodal terminalComputers in Industry10.1016/j.compind.2016.07.00682:C(196-204)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.compind.2016.07.006
Nahas NNourelfath M(2014)Nonlinear threshold accepting meta-heuristic for combinatorial optimisation problemsInternational Journal of Metaheuristics10.1504/IJMHEUR.2014.0689043:4(265-290)Online publication date: 1-Apr-2014
https://dl.acm.org/doi/10.1504/IJMHEUR.2014.068904
Marinakis Y(2012)Multiple Phase Neighborhood Search-GRASP for the Capacitated Vehicle Routing ProblemExpert Systems with Applications: An International Journal10.1016/j.eswa.2012.01.01539:8(6807-6815)Online publication date: 1-Jun-2012
https://dl.acm.org/doi/10.1016/j.eswa.2012.01.015
Marinakis YMarinaki M(2010)A hybrid genetic - Particle Swarm Optimization Algorithm for the vehicle routing problemExpert Systems with Applications: An International Journal10.1016/j.eswa.2009.06.08537:2(1446-1455)Online publication date: 1-Mar-2010
https://dl.acm.org/doi/10.1016/j.eswa.2009.06.085
Kytöjoki JNuortio TBräysy OGendreau M(2007)An efficient variable neighborhood search heuristic for very large scale vehicle routing problemsComputers and Operations Research10.1016/j.cor.2005.10.01034:9(2743-2757)Online publication date: 1-Sep-2007
https://dl.acm.org/doi/10.1016/j.cor.2005.10.010

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