摘要
针对虚拟企业生产计划的特点,以各成员企业承担的生产任务为对象,以快速响应市场为目标,建立了生产任务计划的数学模型,并基于该模型,提出一种基于遗传算法与模拟退火算法混合的求解算法,充分发挥了遗传算法良好的全局搜索能力和模拟退火算法有效避免陷入局部极小的优点,从而提高了算法的全局寻优能力.数值仿真计算表明了该算法的良好收敛性和有效性.
Aiming at the special feature of virtual enterprises（VE）, taking into account the information of tasks that partners undertake and considering quickly responding to market as optimizing objective, a mathematical model is proposed. Based on this model, a hybrid genetic algorithms （HGA） is presented. It makes full use of the excellent whole search ability of genetic algorithm （GA）, and the advantage of simulated annealing algorithm（SA） can avoid getting into part minimum efficiently, thus the global searching ability of HGA is improved. The numerical simulation shows the good convergence and effectiveness of this algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2007年第8期931-934,938,共5页
Control and Decision
基金
国家自然科学基金项目(70572060)
教育部高等学校博士点专项科研基金项目(20040533057)
关键词
虚拟企业
生产计划
遗传算法
模拟退火
Virtual enterprises
Production planning
Genetic algorithm
Simulated annealing
