摘要
针对目前钢铁热轧计划排程中未考虑板坯间电耗变化而造成能耗较高问题,建立基于混合奖金收集模式车辆路径问题(Hybrid Price Collect Vehicle Routing Problem,HPCVRP)的多目标优化模型。针对最小轧制计划数量、工艺规程、吨钢电耗等目标,采用过滤器方法处理热轧模型约束,通过改进的可行性优先粒子比较准则进行最优粒子选择,结合过滤器拥挤距离及拥挤向量机制控制外部档案数量并更新全局最优值,构建过滤器方法的多目标粒子群算法(Filter-MOPSO,FMOPSO),仿真结果表明可以获得良好的Pareto优化前端。最后与人工结果相比,所提算法和模型能够有效解决热轧计划排程问题,为热轧计划编制人员提供良好的决策支持。
Aiming at the high energy consumption caused by disregarding the change between the power consumption of slab, the hot milling planning was formulated as a hybrid multi-objective prize collecting vehicle routing problem（ Hybrid Price Collect Vehicle Routing Problem, HPCVRP） model. The model considers minimum number of rolling plan, production process constrains, and energy consumption. Combine improved feasibility priority particle comparison criteria to select the best particle, and control the number of external files with update the global optimum algorithm by filter crowding distance and congestion vector mechanism for FMOPSO （Filter-MOPSO）. The simulation results indicated that this algorithm could get good distributed Pareto optimal front. The proposed method has been applied in a hot mill line to verify its availability and feasibility by comparing tbe manual scheduling results, which provide decision support for hot milling planner in practical work assignments.
作者
王宸
杨洋
周学良
王生怀
Wang Chen Yang Yang Zhou Xueliang Wang Shenghuai(Shanghai Key Laboratory of Intelligent Manufacturing and Robotics, Shanghai University, Shanghai 200072, China Dept. of Mechanical Engineering, Hubei University of Automotive Technology, Shiyan 442002, Hubei, China)
出处
《现代制造工程》
CSCD
北大核心
2017年第4期102-109,共8页
Modern Manufacturing Engineering
基金
湖北省自然科学基金项目(D2016CFB402)
湖北省自然科学基金项目(2013CFB045)
湖北省教育厅重点项目(D20141802)
湖北省教育厅指导性项目(B2016084)
