摘要
针对热轧圆钢的生产订单接受问题,考虑实际生产中订单提前完工惩罚和返工惩罚的影响,建立了以最大化订单总收益为优化目标的数学模型,提出了基于改进NEH算法和改进和声搜索(MHS)算法相结合的混合算法。首先改进了NEH算法用来产生初始解,再基于和声搜索算法对初始解进行优化,并引入了教与学优化(TLBO)算法思想来对和声向量进行选择和更新,进而控制迭代过程中产生的新解。同时,为了平衡算法的广度和深度搜索能力,在求解过程中动态地调整参数来保证算法的全局优化能力。基于实际生产数据的仿真实验表明,所提算法能有效提高订单总收益和订单接受率,验证了模型和算法的可行性和有效性。
According to the influence of earliness and reworking penalties, the production order acceptance problem of hot-rolled bar was studied. A mathematical model with the objective of maximize gross profit of order was proposed. A hybrid algorithm with improved NEH （Nawaz-Enscore-Ham） algorithm and Modified Harmony Search （MHS） algorithm was proposed for the model. With the consideration of the constraints in the model, an initial solution was generated by the improved NEH algorithm and further optimized by MHS algorithm. Furthermore, the idea of Teaching-Learning-Based Optimization （TLBO） was introduced to the process of selection and updating for harmony vector to take control of the acceptance of new solutions. Meanwhile, in order to balance the breadth and depth of this algorithm＇s searching ability, the parameters were adjusted dynamically to improve the global optimization ability. The simulation experiments with practical production data show that the proposed algorithm can effectively improve total profit and acceptance rate, and validate the feasibility and effectiveness of the model and algorithm.
出处
《计算机应用》
CSCD
北大核心
2014年第8期2419-2423,共5页
journal of Computer Applications
基金
国家自然科学基金资助项目(71231001)
中央高校基本科研业务费专项资金资助项目(FRF-SD-12-011B
FRF-SD-12-012B)
教育部博士学科点专项科研基金资助项目(20100006110006)
关键词
订单接受
热轧圆钢
提前完工
和声搜索
混合算法
order acceptance
hot-rolled bar
earliness
Harmony Search （HS）
hybrid algorithm
