基于改进算法的工艺规划与车间调度的双目标优化模型  

Bi-objective Optimization Model for Integrated Process Planning and Scheduling Based on Improved Algorithm

作　　者：黄志清[1] 唐敦兵[1] 戴敏[1] 

机构地区：[1]南京航空航天大学机电学院,南京210016

出　　处：《南京航空航天大学学报》2015年第1期88-95,共8页Journal of Nanjing University of Aeronautics & Astronautics

基　　金：国家自然科学基金(51175262)资助项目;江苏省杰出青年基金(SBK201210111)资助项目;江苏省产学研前瞻基金(SBY201220116)资助项目

摘　　要：针对工艺规划与车间调度的集成问题,一般考虑以加工时间、加工成本和加工质量为优化性能指标,而对能量消耗等环境影响因素考虑不足。本文建立了工艺规划与车间调度的数学模型,以完工时间和能量消耗为优化目标,通过设置权重系数来调节优化目标倾向。采用改进的混合模拟退火与遗传算法对问题进行求解,利用遗传算法的全局搜索速度快和模拟退火的突跳性强的特点,结合回火机制,有效地得到了完工时间和能量优化结果。最后,通过实例仿真表明该方法具有可行性。In general, the processing time, the processing costs and the processing quality are considered as production performance indicators for integrated process planning and shop scheduling problem. However, the environmental impact such as energy consumption is not taken into account completely. In this paper, a mathematical model for process planning and shop scheduling is established for optimi- zing completion time and energy consumption by changing the weighting factors. An improved hybrid simulated annealing and genetic algorithm is adopted to solve the problem, which is based on the strength of global search for genetic algorithm and local search for simulated annealing. Finally, a case study is given. The experimental result shows that the approach is feasible and efficient.

关 键 词：工艺规划与车间调度 能量消耗 模拟退火 遗传算法 

分 类 号：TH166[机械工程—机械制造及自动化]