In response to the current decline in housing sales, Zhengzhou, capital of central China’s Henan Province, issued 17 measures to boost the local property market in late October. The local government announced that it...In response to the current decline in housing sales, Zhengzhou, capital of central China’s Henan Province, issued 17 measures to boost the local property market in late October. The local government announced that it would purchase unsold apartments and then give them to low-income families who are eligible for public housing.展开更多
Procurement planning with discrete time varying demand is an important problem in Enterprise Resource Planning （ERP）. It can be described using the non-analytic mathematical programming model proposed in this paper....Procurement planning with discrete time varying demand is an important problem in Enterprise Resource Planning （ERP）. It can be described using the non-analytic mathematical programming model proposed in this paper. To solve the model we propose to use a fuzzy decision embedded genetic algorithm. The algorithm adopts an order strategy selection to simplify the original real optimization problem into binary ones. Then, a fuzzy decision quantification method is used to quantify experience from planning experts. Thus, decision rules can easily be embedded in the computation of genetic operations. This approach is applied to purchase planning problem in a practical machine tool works, where satisfactory results have been achieved.展开更多
文摘In response to the current decline in housing sales, Zhengzhou, capital of central China’s Henan Province, issued 17 measures to boost the local property market in late October. The local government announced that it would purchase unsold apartments and then give them to low-income families who are eligible for public housing.
基金This work was supported by Hong Kong Polytechnic University(No.G.45.37.T363),the National Natural Science Foundation of PRC(No.70431003,60521003).
文摘Procurement planning with discrete time varying demand is an important problem in Enterprise Resource Planning （ERP）. It can be described using the non-analytic mathematical programming model proposed in this paper. To solve the model we propose to use a fuzzy decision embedded genetic algorithm. The algorithm adopts an order strategy selection to simplify the original real optimization problem into binary ones. Then, a fuzzy decision quantification method is used to quantify experience from planning experts. Thus, decision rules can easily be embedded in the computation of genetic operations. This approach is applied to purchase planning problem in a practical machine tool works, where satisfactory results have been achieved.
