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作 者:吉清凯 胡祥培[3] 赵达[1] JI Qing-kai;HU Xiang-pei;ZHAO Da(School of Management, Hainan University, Haikou 570228, China;School of Economics andManagement, Southeast University, Nanjing 211189, China;School of Economics and Management, Dalian University of Technology, Dalian 116024, China)
机构地区:[1]海南大学管理学院,海南海口570228 [2]东南大学经济管理学院,江苏南京211189 [3]大连理工大学经济管理学院,辽宁大连116024
出 处:《运筹与管理》2022年第1期8-13,共6页Operations Research and Management Science
基 金:国家自然科学基金资助项目(72061009,71701057,71861009);海南省基础与应用基础研究计划(自然科学领域)高层次人才项目资助(2019RC124);海南省高等学校教育教学改革研究资助项目(Hnjg2020-7)。
摘 要:针对两类供应风险(不确定产能与随机产出率)下装配制造商的零部件订购决策这一难题,运用随机非线性规划方法,以装配商期望利润最大化为目标,建立零部件订购决策的多维优化模型,刻画了确定需求下的最优订购量,并对其进行了灵敏性分析。最后,通过数值算例验证了模型结论并进一步探讨不同类供应风险的影响,为装配商的零部件订购决策和风险管理提供有益的管理启示。For the complex components ordering problem of an assembler with two types of supply uncertainties(component 1 has uncertain production capacity and component 2 has random yield rate),using stochastic nonlinear programming,we present a multidimensional optimization model in which the object is to maximize the assembler’s expected profit.Under deterministic demand,the optimal ordering policyis characterized and sensitivity analysis is provided.We show that theassembler’s expected profit function is concave in a specific zone,in which the optimal ordering amounts are located.The ratio of two components’optimal ordering amounts happens to be a constant,which depends on component 2’s random yield distribution and component 1’s production cost.We prove that improving component 1’s production capacity(stochastically)generally leads to increase in both components’optimal ordering amounts.However,surprisingly,improving component 2’s random yield may lead to non-monotone changes in the components’optimal ordering amounts.Numerical experiments are conducted to justify the model and to further explore the effect of supply uncertainties.Valuable management insights are generated to help the assembler in making ordering decisions and managing supply risks.
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