A Variable Neighbourhood Search Algorithm for Job Shop Scheduling Problems

Abstract. Variable Neighbourhood Search (VNS) is one of the most recent metaheuristics used for solving combinatorial optimization problems in which a systematic change of neighbourhood within a local search is carried out. In this paper, a variable
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  Lecture Notes in Computer Science 3906 Commenced Publication in 1973 Founding and Former Series Editors:Gerhard Goos, Juris Hartmanis, and Jan van Leeuwen Editorial Board David Hutchison  Lancaster University, UK  Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK  Jon M. Kleinberg Cornell University, Ithaca, NY, USA Friedemann Mattern  ETH Zurich, Switzerland  John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland  C. Pandu Rangan  Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan  Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos  NewYork University, NY, USA Doug Tygar University of California, Berkeley, CA, USA MosheY. Vardi  Rice University, Houston, TX, USA Gerhard Weikum  Max-Planck Institute of Computer Science, Saarbruecken, Germany  Jens Gottlieb Günther R. Raidl (Eds.) EvolutionaryComputationin CombinatorialOptimization 6th European Conference, EvoCOP 2006Budapest, Hungary,April 10-12, 2006Proceedings  1 3  Volume EditorsJens GottliebSAPAGDietmar-Hopp-Allee 16, 69190 Walldorf, GermanyE-mail: jens.gottlieb@sap.comGünther R. RaidlVienna University of Technology, Institute of Computer GraphicsAlgorithms and Datastructures GroupFavoritenstr. 9-11/186, 1040 Vienna,AustriaE-mail: cover illustration is the work of Pierre GrenierLibrary of Congress Control Number: 2006922468CR Subject Classification (1998): F.1, F.2, G.1.6, G.2.1, G.1LNCS Sublibrary: SL 1 – Theoretical Computer Science and General IssuesISSN 0302-9743ISBN-10 3-540-33178-6 Springer Berlin Heidelberg NewYork ISBN-13 978-3-540-33178-0 Springer Berlin Heidelberg NewYork  This work is subject to copyright. All rights are reserved, whether the whole or part of the material isconcerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting,reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publicationor parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965,in its current version, and permission for use must always be obtained from Springer. Violations are liableto prosecution under the German Copyright Law.Springer is a part of Springer Science+Business© Springer-Verlag Berlin Heidelberg 2006Printed in GermanyTypesetting: Camera-ready by author, data conversion by Scientific Publishing Services, Chennai, IndiaPrinted on acid-free paper SPIN: 11730095 06/3142 5 4 3 2 1 0  Preface Metaheuristics have often been shown to be effective for difficult combinatorialoptimization problems appearing in various industrial, economical, and scientificdomains. Prominent examples of metaheuristics are evolutionary algorithms,simulated annealing, tabu search, scatter search, memetic algorithms, variableneighborhood search, iterated local search, greedy randomized adaptive searchprocedures, estimation of distribution algorithms, and ant colony optimization.Successfully solved problems include scheduling, timetabling, network design,transportation and distribution problems, vehicle routing, the traveling sales-person problem, satisfiability, packing and cutting problems, planning problems,and general mixed integer programming.The EvoCOP event series started in 2001 and has been held annually sincethen. It was the first specifically dedicated to the application of evolutionarycomputation and related methods to combinatorial optimization problems. Evo-lutionary computation involves the study of problem-solving and optimizationtechniques inspired by principles of natural evolution and genetics. Followingthe general trend of hybrid metaheuristics and diminishing boundaries betweenthe different classes of metaheuristics, EvoCOP has broadened its scope over thelast years and invited submissions on any kind of metaheuristic for combinatorialoptimization problems.This volume contains the proceedings of EvoCOP 2006, the 6th EuropeanConference on Evolutionary Computation in Combinatorial Optimization. It washeld in Budapest, Hungary, on April 10–12 2006, jointly with EuroGP 2006, the9th European Conference on Genetic Programming, and EvoWorkshops 2006,which consisted of the following seven individual workshops: EvoBIO, the 4thEuropean Workshop on Evolutionary Bioinformatics; EvoCOMNET, the ThirdEuropean Workshop on Evolutionary Computation in Communications, Net-works, and Connected Systems; EvoHOT, the Third European Workshop onHardware Optimization; EvoIASP, the 8th European Workshop on Evolution-ary Computation in Image Analysis and Signal Processing; EvoInteraction, theFirst European Workshop on Interactive Evolution and Humanized Computa-tional Intelligence; EvoMUSART, the 4th European Workshop on EvolutionaryMusic and Art; and EvoSTOC, the Third European Workshop on EvolutionaryAlgorithms in Stochastic and Dynamic Environments.EvoCOP, srcinally held as an annual workshop, became a conference in 2004.The events gave researchers an excellent opportunity to present their latest re-search and to discuss current developments and applications, besides stimulatingcloser future interaction between members of this scientific community. Acceptedpapers of previous events were published by Springer in the series  Lecture Notes in Computer Science   (LNCS – Volumes 2037, 2279, 2611, 3004, and 3448).  VI Preface EvoCOP submitted accepted acceptance ratio2001 31 23 74.2%2002 32 18 56.3%2003 39 19 48.7%2004 86 23 26.7%2005 66 24 36.4%2006 77 24 31.2%The rigorous, double-blind reviewing process of EvoCOP 2006 resulted in astrong selection among the submitted papers; the acceptance rate was 31.2%.Each paper was reviewed by at least three members of the international ProgramCommittee. All accepted papers were presented orally at the conference and areincluded in this proceedings volume. We would like to give credit to the membersof our Program Committee, to whom we are very grateful for their quick andthorough work and the valuable advice on how to improve papers for the finalpublication.EvoCOP 2006 covers evolutionary algorithms as well as various other meta-heuristics, like scatter search, tabu search, memetic algorithms, variable neigh-borhood search, greedy randomized adaptive search procedures, ant colonyoptimization, and particle swarm optimization algorithms. The contributionsare dealing with representations, heuristics, analysis of problem structures, andcomparisons of algorithms. The list of studied combinatorial optimization prob-lems includes prominent examples like graph coloring, knapsack problems, thetraveling salesperson problem, scheduling, graph matching, as well as specificreal-world problems.We would like to express our sincere gratitude to the two internationallyrenowned invited speakers, who gave the keynote talks at the conference: RichardJ. Terrile, astronomer, Director, of the Center for Evolutionary Computationand Automated Design at NASA’s Jet Propulsion Laboratory, and Stefan Voß,Chair and Director of the Institute of Information Systems at the University of Hamburg.The success of the conference resulted from the input of many people towhom we would like to express our appreciation. We would like to thank PhilippNeuner for administrating the Web-based conference management system. Thelocal organizers and Judit Megyery did an extraordinary job for which we arevery grateful. Last but not least, the tremendous effort of Jennifer Willies and theSchool of Computing, Napier University, in the administration and coordinationof EuroGP 2006, EvoCOP 2006, and EvoWorkshops 2006 was of paramountimportance.April 2006 Jens GottliebG¨unther R. Raidl
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