This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can...This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.展开更多
Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In ...Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.展开更多
针对基于自主移动机器人(Autonomous Mobile Robot,AMR)的货到人拣选系统多拣货台场景,研究订单分配、处理顺序及货架访问顺序的集成优化,提出多拣货台订单分配与排序问题(Order Allocation and Sequencing Problem,OASP),对订单如何分...针对基于自主移动机器人(Autonomous Mobile Robot,AMR)的货到人拣选系统多拣货台场景,研究订单分配、处理顺序及货架访问顺序的集成优化,提出多拣货台订单分配与排序问题(Order Allocation and Sequencing Problem,OASP),对订单如何分配给拣货台、订单在拣货台的处理顺序及如何安排货架的访问顺序进行集成优化决策,并以最小化订单拣选时间为目标建立混合整数规划模型.设计变邻域搜索算法(the Variable Neighborhood Search Algorithm,VNSA),通过订单相似度进行分批分配并生成贪婪初始解,结合货架置换、订单重分配的抖动算子和订单交换/插入、货架序列调整等4种局部优化邻域,采用动态切换机制实现迭代寻优,并将设计的算法与CPLEX求解器进行比较.研究结果表明:VNSA算法在小规模算例中求解速度与精度优于CPLEX求解器;在大规模算例中对初始解的优化能力显著,验证了联合优化订单分配和排序的有效性;订单拣选时间与拣货台数量、容量呈负相关,与负载平衡系数呈正相关.展开更多
文摘This paper presents a parallel composite local search algorithm based on multiple search neighborhoods to solve a special kind of timetable problem. The new algorithm can also effectively solve those problems that can be solved by general local search algorithms. Experimental results show that the new algorithm can generate better solutions than general local search algorithms.
基金Supported by National Natural Science Foundation of China(Grant Nos.51275366,50875190,51305311)Specialized Research Fund for the Doctoral Program of Higher Education of China(Grant No.20134219110002)
文摘Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.
