DocumentCode
1747784
Title
Sitting guests at a wedding party: experiments on genetic and evolutionary constrained optimization
Author
Rocha, Miguel ; Mendes, Rui ; Cortez, Paulo ; Neves, José
Author_Institution
Departamento de Informatica, Univ. do Minho, Braga, Portugal
Volume
1
fYear
2001
fDate
2001
Firstpage
671
Abstract
The complex task of giving out tables to guests, according to their preferences, at a wedding party, instantiates a broader class of clustering problems, whose purpose is to group a number of entities into a number of clusters, according to a set of hard constraints, and optimizing an objective function. In order to study the application of genetic and evolutionary algorithms (GEAs) to these class of problems, some experiments were conducted. These contemplated different approaches to constraint handling, namely the use of penalty functions and decoders. The encoding issue was also studied, being compared direct and indirect representations of the problem´s solutions in the chromosomes. The development of hybrid genetic operators, that combine the synergies of the GEAs paradigm with those of problem dependent heuristics, were also taken into account. The overall result is a study on the performance of several approaches to constrained optimization by GEAs, that can be used to guide the application of the paradigm in real-world problems, in the combinatorial optimization arena
Keywords
constraint handling; genetic algorithms; operations research; resource allocation; chromosomes; clustering problems; combinatorial optimization; constraint handling; evolutionary algorithms; evolutionary constrained optimization; experiments; genetic algorithms; heuristics; hybrid genetic operators; objective function; party guest sitting problem; penalty functions; Clustering algorithms; Constraint optimization; Decoding; Encoding; Evolutionary computation; Genetics;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location
Seoul
Print_ISBN
0-7803-6657-3
Type
conf
DOI
10.1109/CEC.2001.934456
Filename
934456
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