A set of model is established to optimize BSW Company’s component stock. By analyzing the company’s current part stock condition in terms of the occupation of capitals in the precondition of continuous production, i...A set of model is established to optimize BSW Company’s component stock. By analyzing the company’s current part stock condition in terms of the occupation of capitals in the precondition of continuous production, it describes how to control the purchase parameters of import parts. The model describes how to adjust slightly product output sequence and how to control the components’ purchase parameters: purchasing risk time and purchase order quantity. Then simulation is developed to illustrate the model.展开更多
In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is d...In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is developed by analyzing the fuzzy total cost. By comparing with other four EOQ formulas, i.e., using the crisp numbers with the highest membership values in classic EOQ formula, using the expected values of fuzzy parameters in classic EOQ formula, using the fuzzy variables in classic EOQ formula and then calculating the expected value, and calculat- ing EOQ by hybrid intelligent algorithm simulation, the effectiveness of this formula Js illustrated.展开更多
文摘A set of model is established to optimize BSW Company’s component stock. By analyzing the company’s current part stock condition in terms of the occupation of capitals in the precondition of continuous production, it describes how to control the purchase parameters of import parts. The model describes how to adjust slightly product output sequence and how to control the components’ purchase parameters: purchasing risk time and purchase order quantity. Then simulation is developed to illustrate the model.
基金Supported by National Natural Science Foundation of China (No. 70971092)
文摘In the economic order quantity （EOQ） model, the decision maker has vague information about holding cost, ordering cost and market demand. With these uncertainties characterized as fuzzy variables, a new formula is developed by analyzing the fuzzy total cost. By comparing with other four EOQ formulas, i.e., using the crisp numbers with the highest membership values in classic EOQ formula, using the expected values of fuzzy parameters in classic EOQ formula, using the fuzzy variables in classic EOQ formula and then calculating the expected value, and calculat- ing EOQ by hybrid intelligent algorithm simulation, the effectiveness of this formula Js illustrated.
