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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >Application of Two-Phase Fuzzy Optimization Approach to Multiproduct Multistage Integrated Production Planning with Linguistic Preference under Uncertainty
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Application of Two-Phase Fuzzy Optimization Approach to Multiproduct Multistage Integrated Production Planning with Linguistic Preference under Uncertainty

机译:两阶段模糊优化方法在不确定条件下具有语言偏好的多产品多阶段集成生产计划中的应用

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This paper tackles the challenges for a production planning problem with linguistic preference on the objectives in an uncertain multiproduct multistage manufacturing environment. The uncertain sources are modelled by fuzzy sets and involve those induced by both the epistemic factors of process and external factors from customers and suppliers. A fuzzy multiobjective mixed integer programming model with different objective priorities is proposed to address the problem which attempts to simultaneously minimize the relevant operations cost and maximize the average safety stock holding level and the average service level. The epistemic and external uncertainty is simultaneously considered and formulated as flexible constraints. By defining the priority levels, a two-phase fuzzy optimization approach is used to manage the preference extent and convert the original model into an auxiliary crisp one. Then a novel interactive solution approach is proposed to solve this problem. An industrial case originating from a steel rolling plant is applied to implement the proposed approach. The numerical results demonstrate the efficiency and feasibility to handle the linguistic preference and provide a compromised solution in an uncertain environment.
机译:本文以不确定的多产品多阶段制造环境中的目标为目标,以语言优先解决了生产计划问题的挑战。不确定性来源通过模糊集建模,涉及过程的认知因素和来自客户和供应商的外部因素所引起的不确定性来源。提出了一种具有不同目标优先级的模糊多目标混合整数规划模型,以解决该问题,该模型试图同时最小化相关运营成本,同时最大化平均安全库存持有水平和平均服务水平。同时考虑认知和外部不确定性,并将其表述为弹性约束。通过定义优先级,使用了两阶段模糊优化方法来管理偏好程度,并将原始模型转换为辅助清晰模型。然后提出了一种新颖的交互式解决方案来解决这个问题。应用源自轧钢厂的工业案例来实施所提出的方法。数值结果证明了在不确定的环境中处理语言偏好并提供折衷解决方案的效率和可行性。

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