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Optimization of multi objective Job Shop Scheduling problems using Firefly algorithm

机译:使用Firefly算法优化多目标作业商店调度问题

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Scheduling is the allocation of resources over time to carry out a collection of tasks assigned in any field of engineering and non engineering. Majority of JSSP are categorized into non deterministic (NP) hard problem because of its complexity. Scheduling are generally solved by using heuristics to obtain optimal or near optimal solutions because problems found in practical applications cannot be solved to optimality using available resources in many cases. Many researchers attempted to solve the problem by applying various optimization techniques. While using traditional methods they observed huge difficulty in solving high complex problems and meta-heuristic algorithms were proved most efficient algorithms to solve various JSSP so far. The objective of this paper i) to make use of a newly developed meta heuristic called Firefly algorithm (FA) because of inspiration on Firefly and its characteristic. ii) To find the combined objective function by determining optimal make span, mean flow time and tardiness of different size problems (using Lawrence 1-40 problems) as a bench marking dataset and to find the actual computational time. iii) The analysis of the experimental results on Firefly algorithm based on computational time is compared with other algorithms.
机译:调度是资源的分配随着时间的推移,在任何工程和非工程领域中执行分配的任务集合。大多数JSSP由于其复杂性而分为非确定性(NP)难题。通常通过使用启发式来获得最佳或接近最佳解决方案的调度,因为在许多情况下,实际应用中发现的问题无法解决以可用资源而解决。许多研究人员通过应用各种优化技术来解决问题。在使用传统方法的同时,他们观察到解决高度复杂问题的巨大困难,并且迄今为止,最有效的算法被证明了最有效的算法来解决各种JSSP。本文的目的i)由于对萤火虫的灵感及其特征,利用新开发的Meta启发式算法(FA)。 ii)通过确定最佳制作跨度,不同尺寸问题的平均流量和迟到的组合目标函数(使用劳伦斯1-40个问题)作为替补标记数据集,找到实际计算时间。 III)与其他算法进行比较了基于计算时间的萤火虫算法对实验结果的分析。

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