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Sequencing and scheduling of job and tool in a flexible manufacturing system using ant colony optimization algorithm

机译:使用蚁群优化算法的柔性制造系统中作业和工具的排序和调度

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摘要

Many optimization problems from the manufacturing systems are very complex in nature and quite hard to solve by conventional optimization techniques. The theme of this paper is to generate an active schedules and optimal sequence of job and tool that can meet minimum makespan schedule for the flexible manufacturing system. It consists of similar work center which is capable of doing many operations. The tools are stored in a common tool magazine that shares with and serves for several work centers to reduce the cost of duplicating tools in each and every work center. This type of manufacturing system is used for a manufacturing environment in which tools are expensive. To achieve the objective, the jobs and tools are sequenced and scheduled. In this work, non-traditional optimization technique such as ant colony optimization (ACO) algorithm are proposed to derive near-optimal solutions which adopt the Extended Giffler and Thompson algorithm for active feasible schedule generation. In this paper, the proposed algorithm is used for solving number of problems taken from the literature. The results available for the various existing algorithms are compared with results obtained by the ACO algorithm. The analysis reveals that ACO algorithm provides better solution with reasonable computational time.
机译:制造系统中的许多优化问题本质上是非常复杂的,并且很难通过常规优化技术解决。本文的主题是生成可满足柔性制造系统最小工期计划的活动计划以及最佳的作业和工具顺序。它由能够执行许多操作的类似工作中心组成。这些工具存储在与多个工作中心共享并用于多个工作中心的通用工具库中,以减少在每个工作中心中复制工具的成本。这种类型的制造系统用于工具昂贵的制造环境。为了实现该目标,需要对作业和工具进行排序和计划。在这项工作中,提出了一种非传统的优化技术,例如蚁群优化(ACO)算法,以推导采用最优Giffler和Thompson算法进行主动可行日程生成的近似最优解。在本文中,所提出的算法用于解决文献中提出的许多问题。将可用于各种现有算法的结果与通过ACO算法获得的结果进行比较。分析表明,ACO算法可以在合理的计算时间内提供更好的解决方案。

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