摘要
在无等待流水车间环境下,考虑订单分批量加工策略的订单接受问题,建立问题的数学模型。由于问题的NP难特性,提出改进的遗传算法对模型进行求解。改进的算法采用正向和反向NEH算法与随机方法产生初始种群,在算法更新过程中将禁忌搜索算法嵌入到遗传算法中来实现局部搜索,避免算法陷入局部最优。最后,算例表明批量划分策略能够有效减少订单的完成时间,实现订单总收益的最大化。通过算法对比,说明了改进遗传算法具有较好的求解效果。
An integer programming model is constructed for the order acceptance problem with lot -spliting in no-wait flow shop.With the NP-hard nature for the problem , an improved genetic algorithm ( IGA) is proposed to solve the model .Unlike the standard GA algorithm , based on the basic NEH algorithm , the modified NEH algorithm , and stochastic method , the IGA presents an efficient initialization scheme to con-struct the initial population .In addition , tabu search for generating neighboring solution is embedded in the IGA to avoid a local optimum .Numerical results indicate the efficiency of lot-splitting in shortening the completion time of orders , which contributes to minimizing order tardiness .Compared with traditional ge-netic algorithm , the proposed approach yields significant improvement in solution quality .
出处
《工业工程》
北大核心
2014年第1期44-49,共6页
Industrial Engineering Journal
基金
教育部博士学科点专项科研基金资助项目(20100006110006)
中央高校基本科研业务费专项资金资助项目(FRFSD-12-011B
FRF-SD-12-012B)
国家自然科学基金资助项目(70771008)
