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首页> 外文期刊>Journal of Theoretical and Applied Information Technology >AN EFFICIENT ARTIFICIAL FISH SWARM ALGORITHM WITH HARMONY SEARCH FOR SCHEDULING IN FLEXIBLE JOB-SHOP PROBLEM
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AN EFFICIENT ARTIFICIAL FISH SWARM ALGORITHM WITH HARMONY SEARCH FOR SCHEDULING IN FLEXIBLE JOB-SHOP PROBLEM

机译：柔性Job-SHOP问题调度的高效人工鱼群调度算法。

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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best solution. When it is the better one, it replaces with the artificial fish swarm solution from which this solution was improvised. Meanwhile the best improvised solutions are carried over to the Harmony Memory. The objective is to minimize a total completion time (makespan) and to make the proposed approach as a portion of the expert and the intelligent scheduling system for remanufacturing decision support. Harmony search algorithm has demonstrated to be efficient, simple and strong optimization algorithm. The ability of exploration in any optimization algorithm is one of the key points. The obtained optimization results show that the proposed algorithm provides better exploitation ability and enjoys fast convergence to the optimum solution. As well, comparisons with the original artificial fish swarm algorithm demonstrate improved efficiency.
机译：柔性作业车间调度问题（FJSP）是柔性制造系统中的一个实例。它被认为是非常复杂的控制。因此，为该问题域生成控制系统是困难的。 FJSP继承了车间作业调度问题的特征。它对排序流程有一个附加的决策级别，该级别允许在工厂中一组可用机器中的任何一台机器上处理操作。在本文中，我们提出了一种具有和谐搜索的人工鱼群算法，用于解决柔性作业车间调度问题。它基于从人工鱼群算法获得的结果中证明的新的和声。将该临时解决方案发送给与总体最佳解决方案进行比较。如果效果更好，则用即兴解决方案中的人工鱼群解决方案代替。同时，最好的简易解决方案将被带入“和谐记忆”。目的是最大程度地减少总完成时间（制造时间），并使建议的方法成为专家和智能调度系统的一部分，以进行再制造决策支持。和谐搜索算法已被证明是一种高效，简单且强大的优化算法。任何优化算法中的探索能力都是关键点之一。获得的优化结果表明，该算法具有较好的开发能力，并能快速收敛到最优解。同样，与原始人工鱼群算法的比较证明了改进的效率。

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