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Bi-level plant selection and production allocation model under type-2 fuzzy demand

机译:类型2模糊需求下的双层工厂选择与生产分配模型。

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This study is concerned with the plant selection and production allocation problem under the background of Original Equipment Manufacturing (OEM), which consists of a single controlling company regarded as the leader and multiple candidate plants as the followers. A bi-level programming model is proposed, where the plant selection optimization problem located at the upper level contains nested production allocation optimization problems positioned at the lower level. In this model, demands are described in terms of type-2 triangular fuzzy numbers. In order to handle the type-2 fuzziness, a general expectation reduction method which incorporates an attitude parameter is developed. This method produces different reduced fuzzy numbers based on varying optimistic-pessimistic degrees of decision makers. Then a parametric model based on cut sets of the reduced fuzzy numbers is put forward to make the original problem solvable. An interactive satisfaction degree method is employed to transform the bi-level model into a single level model and produce solutions. Finally, an illustrative example is presented to demonstrate the feasibility of the proposed model and the developed approach. Detailed sensitivity analysis is provided as well. The results show that the attitude of a decision maker has an affect on the objective values at both levels: if the decision maker is more optimistic about the demand, then larger objective values can be obtained. We also find that different settings of satisfaction degree will result in different strategies of plant selection and order allocation. If we want to increase the upper level satisfaction degree, then the lower level satisfaction degree need to be sacrificed. (C) 2017 Elsevier Ltd. All rights reserved.
机译:这项研究涉及原始设备制造(OEM)背景下的工厂选择和生产分配问题,原始设备制造(OEM)由单个控制公司作为领导者,多个候选工厂作为跟随者。提出了一个双层规划模型,其中位于较高级别的工厂选择优化问题包含位于较低级别的嵌套生产分配优化问题。在此模型中,用类型2三角模糊数描述需求。为了处理类型2的模糊性,开发了一种结合了姿态参数的一般期望降低方法。该方法根据决策者的不同乐观悲观程度产生不同的减少的模糊数。然后,提出了基于减少模糊数割集的参数化模型,以解决原始问题。采用交互式满意程度方法将双层模型转换为单层模型并产生解决方案。最后,给出了一个说明性的例子来说明所提出的模型和所开发的方法的可行性。还提供了详细的灵敏度分析。结果表明,决策者的态度在两个层面上都对目标值产生影响:如果决策者对需求更为乐观,则可以获得更大的目标值。我们还发现,满意度的不同设置将导致不同的工厂选择和订单分配策略。如果我们想提高上级满意度,那么就必须牺牲下级满意度。 (C)2017 Elsevier Ltd.保留所有权利。

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