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Application of interactive possibilistic linear programming to aggregate production planning with multiple imprecise objectives

机译:交互式可能线性规划在具有多个不精确目标的总体生产计划中的应用

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摘要

Aggregate production planning (APP) addresses matching supply to forecast demand, with varying customer orders over the intermediate planning horizon. In real-world APP problems, input data and related parameters are commonly imprecise because information is incomplete or unavailable, and the decision maker (DM) must simultaneously consider conflicting objectives. This study develops an interactive possibilistic linear programming (i-PLP) approach to solve multi-product and multi-time period APP problems with multiple imprecise objectives and cost coefficients by triangular possibility distributions in uncertain environments. The imprecise multi-objective APP model designed here seeks to minimise total production costs and changes in work-force level with reference to imprecise demand, cost coefficients, available resources and capacity. Additionally, the proposed i-PLP approach provides a systematic framework that helps the decision-making process to solve fuzzy multi-objective APP problems, enabling a DM to interactively modify the imprecise data and parameters until a set of satisfactory solutions is derived. An industrial case demonstrates the feasibility of applying the proposed approach to a practical multi-objective APP problem.
机译:总体生产计划(APP)解决了将供应与预测需求匹配的问题,在中间计划范围内客户订单有所变化。在实际的APP问题中,输入信息和相关参数通常不准确,因为信息不完整或不可用,决策者(DM)必须同时考虑相互矛盾的目标。这项研究开发了一种交互式的可能性线性规划(i-PLP)方法,通过不确定环境中的三角形可能性分布来解决具有多个不精确目标和成本系数的多产品和多时段APP问题。此处设计的不精确的多目标APP模型旨在参考不精确的需求,成本系数,可用资源和产能,将总生产成本和劳动力水平的变化降至最低。此外,提出的i-PLP方法提供了一个系统的框架,可帮助决策过程解决模糊的多目标APP问题,使DM可以交互地修改不精确的数据和参数,直到得出令人满意的解决方案。一个工业案例证明了将建议的方法应用于实际的多目标APP问题的可行性。

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