The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the ...The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.展开更多
An effective heuristic algorithm for solving the minimum makespan problem of job shop scheduling is presented. With a given feasible solution as a start point, we use Taboo Search technique to get a schedule for each ...An effective heuristic algorithm for solving the minimum makespan problem of job shop scheduling is presented. With a given feasible solution as a start point, we use Taboo Search technique to get a schedule for each neighbor of all its neighbors, and select the best one of the schedules as the new start point. We repeat the procedure, unless the new start point is not better than the proceeding one. To make sure of better results, we introduce reverse technique to the algorithm as well. The computational experiments of the 45 standard instances show that our algorithm yields better results than TSAB algorithm.展开更多
In this paper, a computational effective heuristic method for solving the minimum makespan problem of job shop scheduling is presented. It is based on taboo search procedure and on the shifting bottleneck procedure us...In this paper, a computational effective heuristic method for solving the minimum makespan problem of job shop scheduling is presented. It is based on taboo search procedure and on the shifting bottleneck procedure used to jump out of the trap of the taboo search procedure. A key point of the algorithm is that in the taboo search procedure two taboo lists are used to forbid two kinds of reversals of arcs, which is a new and effective way in taboo search methods for job shop scheduling. Computational experiments on a set of benchmark problem instances show that, in several cases, the approach, in reasonable time, yields better solutions than the other heuristic procedures discussed in the literature.展开更多
针对入侵检测中数据特征维度高的问题,提出了改进粒子群联合禁忌搜索(IPSO-TS)的特征选择算法。采用遗传算子对粒子群算法进行了改进,得到了特征选择初始最优解;对该解进行禁忌搜索(TS)得到了特征子集的全局优化解。基于KDD CUP 99数据...针对入侵检测中数据特征维度高的问题,提出了改进粒子群联合禁忌搜索(IPSO-TS)的特征选择算法。采用遗传算子对粒子群算法进行了改进,得到了特征选择初始最优解;对该解进行禁忌搜索(TS)得到了特征子集的全局优化解。基于KDD CUP 99数据集的实验结果表明,相较遗传算子整合粒子群算法(CMPSO)、粒子群算法(PSO)和粒子群联合禁忌算法,IPSO-TS减少了至少29.2%的特征,缩短了至少15%的平均检测时间,提高了至少2.96%的平均分类准确率。展开更多
基金Supported by Independent Innovation Foundation of Shandong University of China(Grant No.2013GN007)
文摘The idle time which is part of the order fulfillment time is decided by the number of items in the zone; therefore the item assignment method affects the picking efficiency. Whereas previous studies only focus on the balance of number of kinds of items between different zones but not the number of items and the idle time in each zone. In this paper, an idle factor is proposed to measure the idle time exactly. The idle factor is proven to obey the same vary trend with the idle time, so the object of this problem can be simplified from minimizing idle time to minimizing idle factor. Based on this, the model of item assignment problem in synchronized zone automated order picking system is built. The model is a form of relaxation of parallel machine scheduling problem which had been proven to be NP-complete. To solve the model, a taboo search algorithm is proposed. The main idea of the algorithm is minimizing the greatest idle factor of zones with the 2-exchange algorithm. Finally, the simulation which applies the data collected from a tobacco distribution center is conducted to evaluate the performance of the algorithm. The result verifies the model and shows the algorithm can do a steady work to reduce idle time and the idle time can be reduced by 45.63% on average. This research proposed an approach to measure the idle time in synchronized zone automated order picking system. The approach can improve the picking efficiency significantly and can be seen as theoretical basis when optimizing the synchronized automated order picking systems.
基金Supported bythe National Basic Research Programof China (973 Pragram G1998030600)
文摘An effective heuristic algorithm for solving the minimum makespan problem of job shop scheduling is presented. With a given feasible solution as a start point, we use Taboo Search technique to get a schedule for each neighbor of all its neighbors, and select the best one of the schedules as the new start point. We repeat the procedure, unless the new start point is not better than the proceeding one. To make sure of better results, we introduce reverse technique to the algorithm as well. The computational experiments of the 45 standard instances show that our algorithm yields better results than TSAB algorithm.
文摘In this paper, a computational effective heuristic method for solving the minimum makespan problem of job shop scheduling is presented. It is based on taboo search procedure and on the shifting bottleneck procedure used to jump out of the trap of the taboo search procedure. A key point of the algorithm is that in the taboo search procedure two taboo lists are used to forbid two kinds of reversals of arcs, which is a new and effective way in taboo search methods for job shop scheduling. Computational experiments on a set of benchmark problem instances show that, in several cases, the approach, in reasonable time, yields better solutions than the other heuristic procedures discussed in the literature.
文摘针对入侵检测中数据特征维度高的问题,提出了改进粒子群联合禁忌搜索(IPSO-TS)的特征选择算法。采用遗传算子对粒子群算法进行了改进,得到了特征选择初始最优解;对该解进行禁忌搜索(TS)得到了特征子集的全局优化解。基于KDD CUP 99数据集的实验结果表明,相较遗传算子整合粒子群算法(CMPSO)、粒子群算法(PSO)和粒子群联合禁忌算法,IPSO-TS减少了至少29.2%的特征,缩短了至少15%的平均检测时间,提高了至少2.96%的平均分类准确率。
