【摘要】 考虑一个制造商和多个供应商的采购与存储问题。多个供应商分别提供多种原材料，采用一种折扣方案，或单品全量折扣，或总量全量折扣，或混合全量折扣。制造商根据供应商提供的原材料品种和折扣方案，考虑不能按时到货的情况下，确定订货量，制定运输和仓储方案，以最小化总体运营成本。受运输过程中多种因素的影响，到货时间存在一定的不确定性，由此引出调货问题。用模糊随机变量表示到货率，建立相应的模糊随机数学优化模型，通过建立模糊随机期望值模型的方法将不确定的模糊随机优化模型转化为确定的混合整数非线性规划模型。给出求解该问题的算法——基于核搜索的启发式算法，对算例求解并证明了算法的可行性与有效性。通过数值实验，对相关参数进行分析，给出其经济解释，为管理者决策提供参考。更多还原

【Abstract】 In this paper, we consider the sourcing and storage process of a manufacturer. The manufacturer sources raw materials from a set of suppliers that offer either a single quantity discount, or a total quantity discount, or a hybrid quantity discount. Manufacturers should not only select suppliers and warehouses according to the different discount schemes offered by the suppliers, but also determine the order volume, transportation flow, and transfer volume with uncertain arrival time. The manufacturer’s goal is to minimize the total cost. We model a fuzzy random mathematical optimization problem by using fuzzy random variables to represent the delivery rate. Besides, the uncertain fuzzy stochastic optimization model is transformed into a certain mixed integer nonlinear programming model by establishing a fuzzy stochastic expected value model. We give an algorithm called heuristic algorithm based on kernel search to solve this problem. The instances are solved and compared with the results obtained by Kirschstein, Meisel’s algorithm and Gurobi solver. The results verify the feasibility and effectiveness of the algorithm. We analyze relevant parameters through numerical experiments and give their economic explanations, which makes convenience for the manufacturer.更多还原