Multi-Objective Combinatorial Optimization Problems and Solution Methods

316 Pages·2022·22.542 MB·English

by  Mehdi Toloo (editor), Siamak Talatahari (editor), Iman Rahimi (editor)

Multi-Objective Combinatorial
Optimization Problems and
Solution Methods

Multi-Objective Combinatorial
Optimization Problems and
Solution Methods
Edited by
Mehdi Toloo
Department of Business Transformation, Surrey Business
School, University of Surrey, Guildford, United Kingdom,
Department of Systems Engineering, Faculty of Economics,
Technical University of Ostrava, Ostrava, Czech Republic,
Department of Operations Management & Business Statistics,
College of Economics, and Political Science,
Sultan Qaboos University, Muscat, Oman
Siamak Talatahari
Department of Civil Engineering, University of Tabriz, Tabriz,
Iran,
School of Civil and Environment Engineering, University of
New South Wales, Sydney, Australia
Iman Rahimi
University of Technology Sydney, Sydney, Australia
AcademicPressisanimprintofElsevier
125LondonWall,LondonEC2Y5AS,UnitedKingdom
525BStreet,Suite1650,SanDiego,CA92101,UnitedStates
50HampshireStreet,5thFloor,Cambridge,MA02139,UnitedStates
TheBoulevard,LangfordLane,Kidlington,OxfordOX51GB,UnitedKingdom
Copyright©2022ElsevierInc.Allrightsreserved.
Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,electronicor
mechanical,includingphotocopying,recording,oranyinformationstorageandretrievalsystem,without
permissioninwritingfromthepublisher.Detailsonhowtoseekpermission,furtherinformationaboutthe
Publisher’spermissionspoliciesandourarrangementswithorganizationssuchastheCopyrightClearanceCenter
andtheCopyrightLicensingAgency,canbefoundatourwebsite:www.elsevier.com/permissions.
ThisbookandtheindividualcontributionscontainedinitareprotectedundercopyrightbythePublisher(other
thanasmaybenotedherein).
Notices
Knowledgeandbestpracticeinthisfieldareconstantlychanging.Asnewresearchandexperiencebroadenour
understanding,changesinresearchmethods,professionalpractices,ormedicaltreatmentmaybecomenecessary.
Practitionersandresearchersmustalwaysrelyontheirownexperienceandknowledgeinevaluatingandusing
anyinformation,methods,compounds,orexperimentsdescribedherein.Inusingsuchinformationormethods
theyshouldbemindfuloftheirownsafetyandthesafetyofothers,includingpartiesforwhomtheyhavea
professionalresponsibility.
Tothefullestextentofthelaw,neitherthePublishernortheauthors,contributors,oreditors,assumeanyliability
foranyinjuryand/ordamagetopersonsorpropertyasamatterofproductsliability,negligenceorotherwise,or
fromanyuseoroperationofanymethods,products,instructions,orideascontainedinthematerialherein.
BritishLibraryCataloguing-in-PublicationData
AcataloguerecordforthisbookisavailablefromtheBritishLibrary
LibraryofCongressCataloging-in-PublicationData
AcatalogrecordforthisbookisavailablefromtheLibraryofCongress
ISBN:978-0-12-823799-1
ForInformationonallAcademicPresspublicationsvisitour
websiteathttps://www.elsevier.com/books-and-journals
Publisher:MaraConner
AcquisitionsEditor:ChrisKatsaropoulos
EditorialProjectManager:MarianaL.Kuhl
ProductionProjectManager:SojanP.Pazhayattil
CoverDesigner:GregHarris
TypesetbyAptara,NewDelhi,India
Dedication
ThisbookisaffectionatelydedicatedtoPeoplewhowanttodevelopandleadothersandmaketheworld
abetterplaceandalsotoOurFamily.
Prof.Toloo
Dr.Talatahari
Dr.Rahimi
Mehdi Toloo is grateful for the partial support that he received for this research from the Czech
ScienceFoundation(GACR:19–13946S).

Contents
Contributors ..................................................................................................xv
EditorsBiography ...........................................................................................xix
Preface .......................................................................................................xxi
Acknowledgments .........................................................................................xxiii
CHAPTER 1 Multiobjective combinatorial optimization problems: social,
keywords, and journal maps 1
Mehdi Toloo, Siamak Talatahari, Amir H. Gandomi and Iman Rahimi
1.1 Introduction 1
1.2 Methodology 1
1.3 Dataandbasicstatistics 2
1.4 Resultsanddiscussion 3
1.4.1 Mappingthecognitivespace 3
1.4.2 Mappingthesocialspace 4
1.5 Conclusionsanddirectionforfutureresearch 7
References 8
CHAPTER 2 The fundamentals and potential of heuristics and metaheuristics
for multiobjective combinatorial optimization problems and
solution methods 9
Ana Carolina Borges Monteiro, Reinaldo Padilha França, Rangel Arthur
and Yuzo Iano
2.1 Introduction 9
2.2 Multiobjectivecombinatorialoptimization 10
2.3 Heuristicsconcepts 12
2.4 Metaheuristicsconcepts 14
2.5 Heuristicsandmetaheuristicsexamples 16
2.5.1 Tabusearch 16
2.6 Evolutionaryalgorithms(EA) 16
2.7 Geneticalgorithms(GA) 17
2.8 Simulatedannealing 18
2.9 Particleswarmoptimization(PSO) 18
2.10 Scattersearch(SS) 19
2.11 Greedyrandomizedadaptivesearchprocedures(GRASP) 19
2.12 Ant-colonyoptimization 19
2.13 Clusteringsearch 20
2.14 Hybridmetaheuristics 20
vii
viii Contents
2.15 Differentialevolution(DE) 21
2.16 Teachinglearning–basedoptimization(TLBO) 21
2.17 Discussion 21
2.18 Conclusions 23
2.19 Futuretrends 24
References 24
CHAPTER 3 A survey on links between multiple objective decision making
and data envelopment analysis 29
Amineh Ghazi and Farhad Hosseinzadeh Lotfi
3.1 Introduction 29
3.2 Preliminarydiscussion 31
3.2.1 Multipleobjectivedecisionmaking 31
3.2.2 Dataenvelopmentanalysis 32
3.3 ApplicationofMODMconceptsintheDEAmethodology 35
3.3.1 ClassicalDEAmodels 35
3.3.2 Targetsetting 37
3.3.3 Valueefficiency 41
3.3.4 Secondarygoalmodels 43
3.3.5 Commonsetofweights 46
3.3.6 DEA-discriminantanalysis 51
3.3.7 Efficientunitsandefficienthyperplanes 54
3.4 ClassificationofusageofDEAinMODM 56
3.4.1 Efficientpoints 56
3.5 Discussionandconclusion 59
References 60
CHAPTER 4 Improved crow search algorithm based on arithmetic
crossover—a novel metaheuristic technique for solving
engineering optimization problems 71
S.N. Kumar, A. Lenin Fred, L. R. Jonisha Miriam,
Parasuraman Padmanabhan, Balázs Gulyás, Ajay Kumar H
and Nisha Dayana
4.1 Introduction 71
4.2 Materialsandmethods 73
4.2.1 Crowsearchoptimization 73
4.2.2 Arithmeticcrossoverbasedongeneticalgorithm 74
4.2.3 HybridCOalgorithm 74
Contents ix
4.3 Resultsanddiscussion 75
4.4 Conclusion 87
Acknowledgments 88
References 88
CHAPTER 5 MOGROM: Multiobjective Golden Ratio Optimization Algorithm 91
A.F. Nematollahi, A. Rahiminejad and B. Vahidi
5.1 Introduction 91
5.1.1 Definitionofmultiobjectiveproblems(MOPs) 92
5.1.2 Literaturereview 93
5.1.3 Backgroundandrelatedwork 93
5.2 GROMandMOGROM 94
5.2.1 MOGROM 95
5.3 Simulationresults,investigation,andanalysis 97
5.3.1 Firstclass 99
5.3.2 Secondclass 101
5.3.3 Thirdclass 103
5.3.4 Fourthclass 111
5.3.5 Fifthclass 113
5.4 Conclusion 116
References 116
CHAPTER 6 Multiobjective charged system search for optimum location
of bank branch 119
Siamak Talatahari, Abolfazl Ranjbar, Mohammad Tolouei and Iman Rahimi
6.1 Introduction 119
6.2 Multiobjectivebackgrounds 120
6.2.1 DominanceandParetoFront 120
6.2.2 Performancemetrics 121
6.3 Utilizedmethods 122
6.3.1 NSGA-IIalgorithm 122
6.3.2 MOPSOalgorithm 122
6.3.3 MOCSSalgorithm 122
6.4 AnalyticHierarchyProcess 124
6.5 Modelformulation 125
6.6 Implementationandresults 127
6.7 Conclusions 131
References 131