Multi-objective evolutionary decision support for design-supplier-manufacturing planning

F. Xue, A. Sanderson, R. Graves
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引用次数: 2

Abstract

Modern enterprises utilize strategic and dynamic partnerships among designers, suppliers, contract manufacturers and customers to achieve efficiency and response to rapidly changing markets. There is a clear need for planning and decision support tools, and the availability of efficient and accurate multi-objective algorithms is critical to this field. This paper poses the distributed product development as a multi-objective assignment problem, and describes a new class of multi-objective optimization algorithms based on the principles of differential evolution. The multi-objective differential evolution (MODE) algorithm is shown to approach Pareto optimal solutions in a wide class of continuous and discrete problems, providing a practical tool for this domain. A case study of real product designs from the printed circuit board industry demonstrates the effectiveness of the discrete MODE algorithm and its potential value in a decision support system for complex product development.
设计-供应商-制造计划的多目标演化决策支持
现代企业利用设计师、供应商、合同制造商和客户之间的战略和动态合作伙伴关系来实现效率并对快速变化的市场做出反应。规划和决策支持工具的需求非常明显,而高效准确的多目标算法的可用性对该领域至关重要。本文将分布式产品开发问题看作一个多目标分配问题,提出了一类基于差分进化原理的多目标优化算法。多目标差分进化(MODE)算法可以在广泛的连续和离散问题中逼近Pareto最优解,为该领域的研究提供了实用工具。通过对印刷电路板行业实际产品设计的案例研究,证明了离散模式算法的有效性及其在复杂产品开发决策支持系统中的潜在价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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