This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. ...This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.展开更多
The batch splitting scheduling problem has recently become a major target in manufacturing systems, and the researchers have obtained great achievements, whereas most of existing related researches focus on equal-size...The batch splitting scheduling problem has recently become a major target in manufacturing systems, and the researchers have obtained great achievements, whereas most of existing related researches focus on equal-sized and consistent-sized batch splitting scheduling problem, and solve the problem by fixing the number of sub-batches, or the sub-batch sizes, or both. Under such circumstance and to provide a practical method for production scheduling in batch production mode, a study was made on the batch splitting scheduling problem on alternative machines, based on the objective to minimize the makespan. A scheduling approach was presented to address the variable-sized batch splitting scheduling problem in job shops trying to optimize both the number of sub-bathes and the sub-batch sizes, based on differential evolution（DE）, making full use of the finding that the sum of values of genes in one chromosome remains the same before and after mutation in DE. Considering before-arrival set-up time and processing time separately, a variable-sized batch splitting scheduling model was established and a new hybrid algorithm was brought forward to solve both the batch splitting problem and the batch scheduling problem. A new parallel chromosome representation was adopted, and the batch scheduling chromosome and the batch splitting chromosome were treated separately during the global search procedure, based on self-adaptive DE and genetic crossover operator, respectively. A new local search method was further designed to gain a better performance. A solution consists of the optimum number of sub-bathes for each operation per job, the optimum batch size for each sub-batch and the optimum sequence of sub-batches. Computational experiments of four test instances and a realistic problem in a speaker workshop were performed to testify the effectiveness of the proposed scheduling method. The study takes advantage of DE＇s distinctive feature, and employs the algorithm as a solution approach, and thereby deepens and enriches the content of batch splitting scheduling.展开更多
We study a two stage queuing model where the server provides two stages of service one by one in succession. We consider reneging to occur when the server is unavailable during the system breakdown or vacation periods...We study a two stage queuing model where the server provides two stages of service one by one in succession. We consider reneging to occur when the server is unavailable during the system breakdown or vacation periods. We concentrate on deriving the steady state solutions by using supplementary variable technique and calculate the mean queue length and mean waiting time. Further some special cases are also discussed and numerical examples are presented.展开更多
针对作业车间环境具有能力受限的批量调度问题(capacitated lot-sizing and scheduling problem,CLSP),提出基于改进蜜獾算法和神经网络的混合优化算法,以此来应对需求和处理时间的不确定性。首先,考虑需求和处理时间受到不确定性影响,...针对作业车间环境具有能力受限的批量调度问题(capacitated lot-sizing and scheduling problem,CLSP),提出基于改进蜜獾算法和神经网络的混合优化算法,以此来应对需求和处理时间的不确定性。首先,考虑需求和处理时间受到不确定性影响,构建基于可满足性模理论的确定性模型,引入安全库存和安全松弛两个弹性参数,以运营总成本最低为优化目标,建立需求不确定下的鲁棒优化模型;其次,提出基于改进蜜獾算法和神经网络的混合算法,利用混沌理论生成伪随机值,估计安全参数的标称值和变化幅度,提高算法速度;最后,进行示例验证,结果表明所提算法可优化调度准则,减小最优性差距,有效解决具有延期订单许可的问题,降低平均短缺成本。展开更多
批加工设备调度是半导体生产线调度的重要组成部分,对半导体生产线性能有重要影响。在综述批加工设备调度研究成果的基础上,提出了同时考虑即将到来工件与下游设备负载情况的半导体生产线批加工设备调度规则(Scheduling Rule for Batch ...批加工设备调度是半导体生产线调度的重要组成部分,对半导体生产线性能有重要影响。在综述批加工设备调度研究成果的基础上,提出了同时考虑即将到来工件与下游设备负载情况的半导体生产线批加工设备调度规则(Scheduling Rule for Batch Processing Machines in Semiconductor Wafer Fabrication Facilities,SRB)。基于三种不同规模的半导体生产线模型,在非批加工设备使用不同的调度规则的情况下,对提出的SRB进行了仿真验证。仿真结果表明,与目前常用的固定加工批量调度规则相比,SRB能够更好的改善半导体生产线性能,获得较高的工件移动步数、产量和准时交货率,以及较低的加工周期。展开更多
文摘This paper employs mathematical modeling and algebraic approach to derive the optimal manufacturing batch size and number of shipment for a vendor-buyer integrated economic production quantity (EPQ) model with scrap. Unlike the conventional method by using differential calculus to determine replenishment lot size and optimal number of shipments for such an integrated system, this paper proposes a straightforward algebraic approach to replace the use of calculus on the total cost function for solving the optimal production- shipment policies. A simpler form for computing long-run average cost for such a vendor- buyer integrated EPQ problem is also provided.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z155)National Natural Science Foundation of China (Grant No. 60970021)Zhejiang Provincial Natural Science Foundation of China (Grant No. Y1090592)
文摘The batch splitting scheduling problem has recently become a major target in manufacturing systems, and the researchers have obtained great achievements, whereas most of existing related researches focus on equal-sized and consistent-sized batch splitting scheduling problem, and solve the problem by fixing the number of sub-batches, or the sub-batch sizes, or both. Under such circumstance and to provide a practical method for production scheduling in batch production mode, a study was made on the batch splitting scheduling problem on alternative machines, based on the objective to minimize the makespan. A scheduling approach was presented to address the variable-sized batch splitting scheduling problem in job shops trying to optimize both the number of sub-bathes and the sub-batch sizes, based on differential evolution（DE）, making full use of the finding that the sum of values of genes in one chromosome remains the same before and after mutation in DE. Considering before-arrival set-up time and processing time separately, a variable-sized batch splitting scheduling model was established and a new hybrid algorithm was brought forward to solve both the batch splitting problem and the batch scheduling problem. A new parallel chromosome representation was adopted, and the batch scheduling chromosome and the batch splitting chromosome were treated separately during the global search procedure, based on self-adaptive DE and genetic crossover operator, respectively. A new local search method was further designed to gain a better performance. A solution consists of the optimum number of sub-bathes for each operation per job, the optimum batch size for each sub-batch and the optimum sequence of sub-batches. Computational experiments of four test instances and a realistic problem in a speaker workshop were performed to testify the effectiveness of the proposed scheduling method. The study takes advantage of DE＇s distinctive feature, and employs the algorithm as a solution approach, and thereby deepens and enriches the content of batch splitting scheduling.
文摘We study a two stage queuing model where the server provides two stages of service one by one in succession. We consider reneging to occur when the server is unavailable during the system breakdown or vacation periods. We concentrate on deriving the steady state solutions by using supplementary variable technique and calculate the mean queue length and mean waiting time. Further some special cases are also discussed and numerical examples are presented.
文摘针对作业车间环境具有能力受限的批量调度问题(capacitated lot-sizing and scheduling problem,CLSP),提出基于改进蜜獾算法和神经网络的混合优化算法,以此来应对需求和处理时间的不确定性。首先,考虑需求和处理时间受到不确定性影响,构建基于可满足性模理论的确定性模型,引入安全库存和安全松弛两个弹性参数,以运营总成本最低为优化目标,建立需求不确定下的鲁棒优化模型;其次,提出基于改进蜜獾算法和神经网络的混合算法,利用混沌理论生成伪随机值,估计安全参数的标称值和变化幅度,提高算法速度;最后,进行示例验证,结果表明所提算法可优化调度准则,减小最优性差距,有效解决具有延期订单许可的问题,降低平均短缺成本。
