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
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;
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
DOI :
10.1109/ICIS.2007.9
