سال انتشار: ۱۳۹۱

محل انتشار: بیستمین کنفرانس سالانه مهندسی مکانیک

تعداد صفحات: ۵

نویسنده(ها):

Morteza Andalib Sahnehsaraee – Master of Science in Mechanical Engineering, National Iranian Gas Company (NIGC);
Mohammad Javad Mahmoodabadi – Ph.D. Student in Mechanical Engineering, University of Guilan;
Ahmad Bagheri – Associated Professor in Mechanical Engineering, University of Guilan

چکیده:

In this paper, first a multiple-crossover genetic algorithm is presented. Its operators such as reproduction, crossover and mutation are introducedcompletely. Some multi-objective benchmark problems are selected to challenge the ability of the proposed method. Optimization is based on the non-dominated sorting idea. Simulation results are presented. The results are compared with true Pareto-optimal solutions to evaluate the performance of the proposed method