This paper considers the economic production quantity （EPQ） problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expec...This paper considers the economic production quantity （EPQ） problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expected value criterion and chance constrained criterion, a fuzzy expected value model （EVM） and a chance constrained programming （CCP） model are constructed. Then fuzzy simulations are employed to estimate the expected value of fuzzy variable and c^-level minimal average cost. In order to solve the CCP model, a particle swarm optimization （PSO） algorithm based on the fuzzy simulation is designed. Finally, the effectiveness of PSO algorithm based on the fuzzy simulation is illustrated by a numerical example.展开更多
基金supported by the National Natural Science Foundation of China under Grant No. 70471049
文摘This paper considers the economic production quantity （EPQ） problem with backorder in which the setup cost, the holding cost and the backorder cost are characterized as fuzzy variables, respectively. Following expected value criterion and chance constrained criterion, a fuzzy expected value model （EVM） and a chance constrained programming （CCP） model are constructed. Then fuzzy simulations are employed to estimate the expected value of fuzzy variable and c^-level minimal average cost. In order to solve the CCP model, a particle swarm optimization （PSO） algorithm based on the fuzzy simulation is designed. Finally, the effectiveness of PSO algorithm based on the fuzzy simulation is illustrated by a numerical example.
