The small world of efficient solutions: empirical evidence from the bi-objective {0,1}-knapsack problem

The small world phenomenon, Milgram (1967) has inspired the study of real networks such as cellular networks, telephone call networks, citation networks, power and neural networks, etc. The present work is about the study of the graphs produced by efficient solutions of the bi-objective {0,1}-knapsa...

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Bibliographic Details
Published in4OR Vol. 8; no. 2; pp. 195 - 211
Main Authors Gomes da Silva, Carlos, Clímaco, João, Filho, Adiel Almeida
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer-Verlag 01.06.2010
Springer Nature B.V
Subjects
Algorithms
Business and Management
Cellular communication
Collaboration
Combinatorial analysis
Graphs
Industrial and Production Engineering
Knapsack problem
Linear programming
Multiple objective analysis
Neural networks
Operations research
Operations Research/Decision Theory
Optimization
Research Paper
{0, 1} Multi-objective combinatorial optimization problems
Networks
90C27
Small world measures
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Summary:The small world phenomenon, Milgram (1967) has inspired the study of real networks such as cellular networks, telephone call networks, citation networks, power and neural networks, etc. The present work is about the study of the graphs produced by efficient solutions of the bi-objective {0,1}-knapsack problem. The experiments show that these graphs exhibit properties of small world networks. The importance of the supported and non-supported solutions in the entire efficient graph is investigated. The present research could be useful for developing more effective search strategies in both exact and approximate solution methods of {0,1} multi-objective combinatorial optimization problems.
ISSN:1619-4500
1614-2411
DOI:10.1007/s10288-009-0110-3