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Concurrent product configuration and process planning, towards an approach combining interactivity and optimality

机译:同时进行产品配置和过程计划,以实现将交互性和最优性相结合的方法

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In mass customisation, defining concurrently the configured product and the planning of the associated production process is a key issue in the customer/supplier relationship. Nevertheless, few studies propose supporting the decision-maker during the resolution of this significant problem. After studying the decision-maker's needs and problem characterisation (modelling and scale aspects), we propose in this paper a two-step approach with the aid of some tools. The first step allows the customer or internal requirements to be captured interactively with a constraint-based approach. However, this step does not lead to one single solution, e.g. there are many uninstantiated remaining decision variables. In this paper, we suggest adding an original optimisation step to complete this task. Thus, the contribution of the study is twofold: first, methodologically to define a new two-step approach that meets industrial needs; and second, to provide adapted tools especially for the optimisation step. The optimisation step, using a multi-criteria constrained evolutionary algorithm, allows the user to select their own cost/cycle time compromise among a set of Pareto optimised solutions. A conventional evolutionary algorithm is adapted and modified, with the inclusion of filtering processing, in order to avoid generating invalid solutions. Experimentations are described, and a comparison is made with a branch-and-bound approach that outlines the interest in the propositions.
机译:在大规模定制中,同时定义配置的产品和相关生产过程的计划是客户/供应商关系中的关键问题。然而,很少有研究建议在解决这一重大问题的过程中为决策者提供支持。在研究了决策者的需求和问题特征(建模和规模方面)之后,我们在本文中借助一些工具提出了一种两步法。第一步允许使用基于约束的方法交互式地捕获客户或内部需求。但是,此步骤不会导致一个单一的解决方案,例如还有许多未实例化的剩余决策变量。在本文中,我们建议添加原始优化步骤以完成此任务。因此,这项研究的贡献是双重的:第一,从方法论上定义满足工业需求的新的两步法。其次,提供专门用于优化步骤的工具。使用多准则约束进化算法的优化步骤允许用户在一组Pareto优化解决方案中选择自己的成本/周期时间折衷方案。为了避免生成无效解,对传统的进化算法进行了修改和修改,其中包括过滤处理。描述了实验,并使用分支定界方法进行了比较,该方法概述了对命题的兴趣。

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