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A SURVEY OF ASSEMBLY PLANNING BASED ON INTELLIGENT OPTIMIZATION ALGORITHMS

机译:基于智能优化算法的装配规划研究

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摘要

Assembly planning is one of the NP complete problems, which is even more difficult to solve for complex products. Intelligent optimization algorithms have obvious advantages to deal with such combinatorial problems. Various intelligent optimization algorithms have been applied to assembly sequence planning and optimization in the last decade. This paper surveys the state-of-the-art of the assembly planning methods based on the intelligent optimization algorithms. Five intelligent optimization algorithms, i.e. genetic algorithm (GA), artificial neural networks (ANN), simulated annealing (SA), ant colony algorithm (ACO) and artificial immune algorithm (AIA), and their applications in assembly planning and optimization are introduced respectively. The application features of the algorithms are summarized. At last, the future research directions of the assembly planning based on the intelligent optimization algorithms are discussed.
机译:组装计划是NP的完整问题之一,对于复杂的产品而言,解决起来甚至更加困难。智能优化算法在解决此类组合问题方面具有明显的优势。在过去的十年中,各种智能优化算法已应用于装配顺序计划和优化。本文概述了基于智能优化算法的最新装配计划方法。分别介绍了遗传算法(GA),人工神经网络(ANN),模拟退火(SA),蚁群算法(ACO)和人工免疫算法(AIA)五种智能优化算法及其在装配计划和优化中的应用。 。总结了算法的应用特点。最后,讨论了基于智能优化算法的装配计划的未来研究方向。

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