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An Improved Ant Colony Optimization Approach for Optimization of Process Planning

机译:一种改进的工艺规划优化蚁群优化方法

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摘要

Computer-aided process planning (CAPP) is an important interface between computer-aided design (CAD) and computer-aided manufacturing (CAM) in computer-integrated manufacturing environments (CIMs). In this paper, process planning problem is described based on a weighted graph, and an ant colony optimization (ACO) approach is improved to deal with it effectively. The weighted graph consists of nodes, directed arcs, and undirected arcs, which denote operations, precedence constraints among operation, and the possible visited path among operations, respectively. Ant colony goes through the necessary nodes on the graph to achieve the optimal solution with the objective of minimizing total production costs (TPCs). A pheromone updating strategy proposed in this paper is incorporated in the standard ACO, which includes Global Update Rule and Local Update Rule. A simple method by controlling the repeated number of the same process plans is designed to avoid the local convergence. A case has been carried out to study the influence of various parameters of ACO on the system performance. Extensive comparative experiments have been carried out to validate the feasibility and efficiency of the proposed approach.
机译:计算机辅助过程规划(CAPP)是计算机集合制造环境(CIMS)中的计算机辅助设计(CAD)和计算机辅助制造(CAM)之间的重要界面。在本文中,基于加权图描述了过程规划问题,并且改善了蚁群优化(ACO)方法以有效地处理。加权图包括节点,定向弧和无向弧,其表示操作之间的操作,优先约束,以及操作中可能的访问路径。蚁群通过图表上的必要节点来实现最佳解决方案,目的是最小化总生产成本(TPC)。本文提出的信息素更新策略纳入标准ACO,其中包括全局更新规则和本地更新规则。通过控制相同的过程计划的重复数量的简单方法旨在避免局部收敛。已经进行了案例,以研究ACO各种参数对系统性能的影响。已经进行了广泛的比较实验,以验证所提出的方法的可行性和效率。

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