Title :
Solving for nonlinear integer programming problem using genetic algorithm and its application
Author :
Yokota, Takao ; Gen, Mitsuo
Author_Institution :
Dept. of Ind. & Syst. Eng., Ashikaga Inst. of Technol., Japan
Abstract :
In general, it is difficult to directly solve an optimization problem of systems reliability formulated as a nonlinear integer programming (NIP) model. In this paper, we propose a method for solving the NIP problem for the best compromise solution while holding a nonlinear property by using the genetic algorithm. We also report that the optimization problem of systems reliability as a case study is solved using the proposed method. The numerical comparison experiments between the 0-1 LP/0-1 NP formulations are demonstrated and, from the quantitative evaluation, the efficiency of the proposed method is demonstrated
Keywords :
genetic algorithms; integer programming; nonlinear programming; efficiency; genetic algorithm; nonlinear integer programming; optimization; systems reliability; Constraint optimization; Design optimization; Ear; Genetic algorithms; Linear programming; Linearity; Optimization methods; Polynomials; Reliability; Time factors; Upper bound;
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
DOI :
10.1109/ICSMC.1994.400076