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Meta-heuristic approaches for flowshop scheduling problems: a review

机译:Flowshop调度问题的元启发式方法:综述

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The right approach towards the optimisation of multi-objective nonlinear problem is the incremental adoption of available techniques and strategies that help to minimise the solution time and to improve the optimised results. Meta-heuristics are heuristic methods that help the search through the solution space using algorithms. Meta-heuristics further improve the solution that comes initially from heuristics. This paper presents various types of meta-heuristics approaches for optimising flowshop scheduling (FSS) with focus on minimising parameters like total tardiness, total earliness, maximum makespan, total no. of tardy jobs, etc. Since the problem is NP-hard, the meta-heuristics and hybrid meta-heuristics are most appropriate methods to solve this kind of problem. Meta-heuristics are projected as strategic means to achieve the optimum and efficient schedule, with positive impact on cost minimisation (economies of scale) and simultaneously reducing solution time.
机译:解决多目标非线性问题的正确方法是逐步采用可用的技术和策略,以帮助最小化求解时间并改善优化结果。元启发式算法是启发式方法,可帮助您使用算法在解决方案空间中进行搜索。元启发式算法进一步改善了最初源自启发式算法的解决方案。本文介绍了用于优化Flowshop调度(FSS)的各种类型的元启发式方法,重点是使总延迟,总提前期,最大制造期限,总编号等参数最小化。由于问题是NP难题,因此元启发法和混合元启发法是解决此类问题的最合适方法。元启发法被认为是实现最佳和高效进度的战略手段,对成本最小化(规模经济)产生积极影响,同时缩短了解决时间。

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