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| 精英改进粒子群算法在入库堆垛问题中的应用 | |
| 引用本文： | 张琦琪,张涛,刘鹏.精英改进粒子群算法在入库堆垛问题中的应用[J].计算机工程与科学,2015,37(7):1311-1317. |
| 作者姓名： | 张琦琪 张涛 刘鹏 |
| 作者单位： | 1. 上海财经大学信息管理与工程学院,上海200433;上海科学技术职业学院,上海201800 2. 上海财经大学信息管理与工程学院,上海200433;上海市金融信息技术研究重点实验室(上海财经大学),上海200433 3. 上海财经大学信息管理与工程学院,上海,200433 |
| 基金项目： | 国家自然科学基金资助项目，教育部高等学校博士学科点专项科研基金资助项目，教育部留学回国人员科研启动基金，上海市哲学社会科学规划项目，上海市金融信息技术研究重点实验室开放课题资助项目 |
| 摘 要： | 针对钢铁企业生产与物流一体化协同管理中入库堆垛问题,基于出库次序A型约束、垛位选择分散性约束等,建立了以均衡库存垛位负载和最大化板坯综合匹配度为目标的联合优化模型。结合问题的特点,基于PSO算法,利用收敛指数判断种群进化状态,并对处于"收敛"状态的种群执行精英学习策略,提高粒子的活性,帮助种群跃出局部最优。最后通过实例仿真说明了模型与算法的有效性和可行性。 |
| 关 键 词： | 入库堆垛问题 粒子群优化 精英学习策略 分散性约束 收敛指数 |
| 收稿时间： | 2014-12-01 |
| 修稿时间： | 2015-07-25 |
Elitist learning strategy: an improved particle swarm optimizer algorithm for stack selection optimization |
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| ZHANG Qi-qi,ZHANG Tao,LIU Peng.Elitist learning strategy: an improved particle swarm optimizer algorithm for stack selection optimization[J].Computer Engineering & Science,2015,37(7):1311-1317. | |
| Authors: | ZHANG Qi-qi ZHANG Tao LIU Peng |
| Affiliation: | (1.School of Information Management and Engineering,Shanghai University of Finance and Economics,Shanghai 200433; 2.Shanghai Vocational College of Science and Technology,Shanghai 201800; 3.Shanghai Key Laboratory of Financial Information Technology, Shanghai University of Finance and Economics,Shanghai 200433,China) |
| Abstract: | To solve the stack selection problem in the integrated management of inventory and production for the iron steel enterprises,we construct a joint optimization model to balance the load of each stack and to maximize the slab comprehensive matching degree at the same time based on the A shaped constraints,dispersive constraints et al.To help the solution jump out of the local optimum during the evolution when using the particle swarm optimization (PSO) algorithm, we introduce an elitist learning strategy,which can improve the solutions when the group converges.Finally,simulation results demonstrate the validity and feasibility of the proposed algorithm. |
| Keywords: | stack selection problem particle swarm optimization elitist learning strategy dispersive constraints exponent of convergence |
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