State-of-the-art in optimisation and heuristics to solve manufacturing scheduling problem

Puja Bharti and Sushma Jain

International Journal of Operational Research, 2022, vol. 44, issue 3, 292-348

Abstract: Manufacturing scheduling is known to be one of the most complex optimisation problems and falls in the category of NP-hard problems. Continuous efforts have been made by the researchers in the past to find convincingly accurate solutions for the instances in a reasonable time. It is valuable to compile the abundant literature available in this area for better understanding as well as convenience. This survey presents a systematic review of the optimisation approaches to solve manufacturing scheduling problem. Primarily, the research published during the period 2001-March 2019 has been considered. For this, a total of 456 research papers were examined. A comprehensive, well-informed examination and realistic analysis of the available literature provides an insight into major developments that has taken place pertaining to the use of heuristics/meta-heuristics in solving this problem. A classification based on objectives, optimisation techniques, benchmark instances, software tools, etc., highlights the research trends in this field along with future directions.

Keywords: optimisation; heuristics; NP-hard; job shop scheduling; review; meta-heuristics; state-of-art; single objective; multi-objective; multi-objective evolutionary algorithms; MOEAs; manufacturing scheduling. (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:44:y:2022:i:3:p:292-348

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