Title :
Effectiveness of penalty function in solving the subset sum problem
Author :
Wang, Hong ; Ma, Zhiqiang ; Nakayama, Kenji
Author_Institution :
Dept. of Electr. & Comput. Eng., Kanazawa Univ., Japan
Abstract :
We investigate the evolutionary heuristics used as approximation algorithm to the subset sum problem. We propose a graded penalty function in a fitness function of genetic algorithms to penalize an infeasible string in solving the subset sum problem. An exponential term of generation variable, t0, is added into the penalty function for increasing penalty generation by generation. The experiments show that the proposed penalty function is more efficient, than other existing penalty functions. It is suggested that the penalty pressure is increased step by step
Keywords :
algorithm theory; combinatorial mathematics; genetic algorithms; heuristic programming; multiprogramming; search problems; storage management; approximation algorithm; evolutionary heuristics; fitness function; generation variable exponential term; genetic algorithms; graded penalty function; infeasible string; penalty function effectiveness; penalty pressure; subset sum problem solving; Constraint optimization; Equations; Genetic algorithms; Space power stations; Springs;
Conference_Titel :
Evolutionary Computation, 1996., Proceedings of IEEE International Conference on
Conference_Location :
Nagoya
Print_ISBN :
0-7803-2902-3
DOI :
10.1109/ICEC.1996.542401