Mass customization (MC) is emerging as a competitive advantage of firms with the intensified competition and economic globalization.As a key feature of MC,postponement strategy postpones activities in the supply chain...Mass customization (MC) is emerging as a competitive advantage of firms with the intensified competition and economic globalization.As a key feature of MC,postponement strategy postpones activities in the supply chain until customer orders are received.This article provides a review of the literature on postponement from perspectives of research content and methodology.Taking postponement as a supply chain concept,this article specifically reclassifies the postponement applications according to the positioning of the customer order decoupling point (CODP) in the supply chain.Future directions for postponement research are also suggested in this article.展开更多
In this paper, we focus on the real-time interactions among multiple utility companies and multiple users and formulate real-time pricing(RTP) as a two-stage optimization problem. At the first stage, based on cost fun...In this paper, we focus on the real-time interactions among multiple utility companies and multiple users and formulate real-time pricing(RTP) as a two-stage optimization problem. At the first stage, based on cost function, we propose a continuous supply function bidding mechanism to model the utility companies’ profit maximization problem, by which the analytic expression of electricity price is further derived. At the second stage, considering that individually optimal solution may not be socially optimal, we employ convex optimization with linear constraints to model the price anticipating users’ daily payoff maximum. Substitute the analytic expression of electricity price obtained at the first stage into the optimization problem at the second stage. Using customized proximal point algorithm(C-PPA), the optimization problem at the second stage is solved and electricity price is obtained accordingly. We also prove the existence and uniqueness of the Nash equilibrium in the mentioned twostage optimization and the convergence of C-PPA. In addition, in order to make the algorithm more practical, a statistical approach is used to obtain the function of price only through online information exchange, instead of solving it directly. The proposed approach offers RTP, power production and load scheduling for multiple utility companies and multiple users in smart grid. Statistical approach helps to protect the company’s privacy and avoid the interference of random factors, and C-PPA has an advantage over Lagrangian algorithm because the former need not obtain the objection function of the dual optimization problem by solving an optimization problem with parameters. Simulation results show that the proposed framework can significantly reduce peak time loading and efficiently balance system energy distribution.展开更多
基金National Natural Science Foundation of ChinaMinistry of Science&Technology of China and Scientific and Technological Innovation Foundation for Graduate Students of Huazhong University of Science and Technology for the financial support through grant 79970026,a National 863/CIMS Scheme grant 2001AA414110 and grant YCJ-02-005 respectively.
文摘Mass customization (MC) is emerging as a competitive advantage of firms with the intensified competition and economic globalization.As a key feature of MC,postponement strategy postpones activities in the supply chain until customer orders are received.This article provides a review of the literature on postponement from perspectives of research content and methodology.Taking postponement as a supply chain concept,this article specifically reclassifies the postponement applications according to the positioning of the customer order decoupling point (CODP) in the supply chain.Future directions for postponement research are also suggested in this article.
基金Supported by the Natural Science Foundation of China(11171221)
文摘In this paper, we focus on the real-time interactions among multiple utility companies and multiple users and formulate real-time pricing(RTP) as a two-stage optimization problem. At the first stage, based on cost function, we propose a continuous supply function bidding mechanism to model the utility companies’ profit maximization problem, by which the analytic expression of electricity price is further derived. At the second stage, considering that individually optimal solution may not be socially optimal, we employ convex optimization with linear constraints to model the price anticipating users’ daily payoff maximum. Substitute the analytic expression of electricity price obtained at the first stage into the optimization problem at the second stage. Using customized proximal point algorithm(C-PPA), the optimization problem at the second stage is solved and electricity price is obtained accordingly. We also prove the existence and uniqueness of the Nash equilibrium in the mentioned twostage optimization and the convergence of C-PPA. In addition, in order to make the algorithm more practical, a statistical approach is used to obtain the function of price only through online information exchange, instead of solving it directly. The proposed approach offers RTP, power production and load scheduling for multiple utility companies and multiple users in smart grid. Statistical approach helps to protect the company’s privacy and avoid the interference of random factors, and C-PPA has an advantage over Lagrangian algorithm because the former need not obtain the objection function of the dual optimization problem by solving an optimization problem with parameters. Simulation results show that the proposed framework can significantly reduce peak time loading and efficiently balance system energy distribution.
