DocumentCode
3109715
Title
A Combined MA-GA Approach for Solving Constrained Optimization Problems
Author
Ullah, Abu Saleh Shah Muhammad Barkat ; Sarker, Ruhul ; Cornforth, David
Author_Institution
Univ. of New South Wales, Canberra
fYear
2007
fDate
11-13 July 2007
Firstpage
382
Lastpage
387
Abstract
Many real world decision processes require to solve optimization problems. In this paper, an integrated multiagent-genetic algorithm (MA-GA) is considered to solve constrained optimization problems. The applied approach is new in the literature for solving constrained optimization problems. Ten benchmark problems are used to test the performance of the approach and the results show impressive performance.
Keywords
decision theory; genetic algorithms; mathematics computing; multi-agent systems; combined MA-GA approach; constrained optimization problem; decision process; integrated multiagent-genetic algorithm; Australia; Computer science; Constraint optimization; Evolutionary computation; Genetic algorithms; Multiagent systems; Problem-solving; Routing; Transportation; Wire; Constrained Optimization; Genetic Algorithms; Multiagent Systems; Nonlinear Programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on
Conference_Location
Melbourne, Qld.
Print_ISBN
0-7695-2841-4
Type
conf
DOI
10.1109/ICIS.2007.9
Filename
4276412
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