Solutions methods for m-machine blocking flow shop with setup times and preventive maintenance costs to minimise hierarchical objective-function

In this article, maintenance operations were incorporated to the sequence-dependent setup blocking flow shop to minimise total completion time subject to total maintenance costs. A mixed integer linear programming and procedures to incorporate maintenance to job sequence were developed. A constructi...

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Vydané v:International journal of production research Ročník 61; číslo 19; s. 6308 - 6335
Hlavní autori: Miyata, Hugo Hissashi, Nagano, Marcelo Seido, Gupta, Jatinder N. D.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Taylor & Francis 02.10.2023
Taylor & Francis LLC
Predmet:
Blocking
blocking flow shop
Completion time
Computational efficiency
Computing time
Greedy algorithms
Heuristic methods
Integer programming
Linear programming
Maintenance costs
maintenance operations
Mixed integer
Preventive maintenance
Scheduling
setup times
Swarm intelligence
total completion time
Tradeoffs
ISSN:0020-7543, 1366-588X
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Shrnutí:In this article, maintenance operations were incorporated to the sequence-dependent setup blocking flow shop to minimise total completion time subject to total maintenance costs. A mixed integer linear programming and procedures to incorporate maintenance to job sequence were developed. A constructive heuristic and three metaheuristics, greedy randomised adaptative search procedure (GRASP), discrete artificial bee colony (DABC), variable block insertion heuristic (VBIH) and iterated greedy algorithm (IG), designed to the blocking flow shop with total completion time minimisation were adapted to minimise total maintenance costs and the hierarchical function, respectively.All the methods were applied to solve small and medium and large size instance sets, with respective 1920 and 2200 problems. Experimental results shows that for small size instances set, DABC with (DABC(20)) obtained the best trade-off between effectiveness and efficiency. For medium and large size instances set, DABC(20) VBIH with (VBIH(20)) generated the best trade-off between quality of solution and computational time. Considering both instances set together, both DABC(20) and VBIH(20) obtained the best performance between quality of solution and computational time.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2022.2127959