PasMoQAP: A parallel asynchronous memetic algorithm for solving the Multi-Objective Quadratic Assignment Problem

Multi-Objective Optimization Problems (MOPs) have attracted growing attention during the last decades. Multi-Objective Evolutionary Algorithms (MOEAs) have been extensively used to address MOPs because are able to approximate a set of non-dominated high-quality solutions. The Multi-Objective Quadrat...

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Veröffentlicht in:2017 IEEE Congress on Evolutionary Computation (CEC) S. 1103 - 1110
Hauptverfasser: Sanhueza, Claudio, Jimenez, Francia, Berretta, Regina, Moscato, Pablo
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2017
Schlagworte:
Algorithm design and analysis
Evolutionary computation
Memetic Algorithms
Memetics
Multi-Objective Optimization
Optimization
Parallel Island Model
Sociology
Statistics
Topology
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Abstract Multi-Objective Optimization Problems (MOPs) have attracted growing attention during the last decades. Multi-Objective Evolutionary Algorithms (MOEAs) have been extensively used to address MOPs because are able to approximate a set of non-dominated high-quality solutions. The Multi-Objective Quadratic Assignment Problem (mQAP) is a MOP. The mQAP is a generalization of the classical QAP which has been extensively studied, and used in several real-life applications. The mQAP is defined as having as input several flows between the facilities which generate multiple cost functions that must be optimized simultaneously. In this study, we propose PASMOQAP, a parallel asynchronous memetic algorithm to solve the Multi-Objective Quadratic Assignment Problem. PASMOQAP is based on an island model that structures the population by creating subpopulations. The memetic algorithm on each island individually evolve a reduced population of solutions, and they asynchronously cooperate by sending selected solutions to the neighboring islands. The experimental results show that our approach significatively outperforms all the island-based variants of the multi-objective evolutionary algorithm NSGA-II. We show that PASMOQAP is a suitable alternative to solve the Multi-Objective Quadratic Assignment Problem.
AbstractList Multi-Objective Optimization Problems (MOPs) have attracted growing attention during the last decades. Multi-Objective Evolutionary Algorithms (MOEAs) have been extensively used to address MOPs because are able to approximate a set of non-dominated high-quality solutions. The Multi-Objective Quadratic Assignment Problem (mQAP) is a MOP. The mQAP is a generalization of the classical QAP which has been extensively studied, and used in several real-life applications. The mQAP is defined as having as input several flows between the facilities which generate multiple cost functions that must be optimized simultaneously. In this study, we propose PASMOQAP, a parallel asynchronous memetic algorithm to solve the Multi-Objective Quadratic Assignment Problem. PASMOQAP is based on an island model that structures the population by creating subpopulations. The memetic algorithm on each island individually evolve a reduced population of solutions, and they asynchronously cooperate by sending selected solutions to the neighboring islands. The experimental results show that our approach significatively outperforms all the island-based variants of the multi-objective evolutionary algorithm NSGA-II. We show that PASMOQAP is a suitable alternative to solve the Multi-Objective Quadratic Assignment Problem.
Author Moscato, Pablo
Jimenez, Francia
Sanhueza, Claudio
Berretta, Regina
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  surname: Sanhueza
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  givenname: Francia
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  organization: School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia
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  givenname: Pablo
  surname: Moscato
  fullname: Moscato, Pablo
  email: pablo.moscato@newcastle.edu.au
  organization: School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia
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Snippet Multi-Objective Optimization Problems (MOPs) have attracted growing attention during the last decades. Multi-Objective Evolutionary Algorithms (MOEAs) have...
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SubjectTerms Algorithm design and analysis
Evolutionary computation
Memetic Algorithms
Memetics
Multi-Objective Optimization
Optimization
Parallel Island Model
Sociology
Statistics
Topology
Title PasMoQAP: A parallel asynchronous memetic algorithm for solving the Multi-Objective Quadratic Assignment Problem
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