流程车间调度问题的元启发式方法:综述

Deepanshu Arora, G. Agarwal
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引用次数: 12

摘要

对多目标非线性问题进行优化的正确方法是逐步采用可用的技术和策略,以帮助最小化解决时间并改善优化结果。元启发式是一种启发式方法,它使用算法帮助搜索解决方案空间。元启发式进一步改进了最初来自启发式的解决方案。本文介绍了优化流水车间调度(FSS)的各种类型的元启发式方法,重点是最小化总延迟、总提前、最大完工时间、总工期等参数。迟到的工作等。由于问题是np困难的,元启发式和混合元启发式是解决这类问题的最合适的方法。元启发式被预测为实现最佳和有效的时间表的战略手段,对成本最小化(规模经济)有积极影响,同时减少解决时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Meta-heuristic approaches for flowshop scheduling problems: a review
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.
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