Multi-objective multi-unit process plan generation in a reconfigurable manufacturing environment: a comparative study of three hybrid metaheuristics

Low costs, high reactivity and high quality products are necessary criteria for industries to achieve competitiveness in nowadays market. In this context, reconfigurable manufacturing systems (RMSs) have emerged to fulfil these requirements. RMS is one of the latest manufacturing paradigms, where ma...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:International journal of production research Ročník 57; číslo 24; s. 7520 - 7535
Hlavní autori: Touzout, Faycal A., Benyoucef, Lyes
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Taylor & Francis 17.12.2019
Taylor & Francis LLC
Predmet:
Classification
Comparative studies
Completion time
Computer Science
Genetic algorithms
Heuristic
iterated local search
Manufacturing
Materials handling
multi-objective optimisation
Multiple objective analysis
NSGA-II
Operations Research
Optimization
process plan generation
Production costs
reconfigurable manufacturing system (RMS)
Reconfiguration
Sorting algorithms
NSGA-II
Process plan generation
Reconfigurable manufacturing system (RMS)
Iterated local search
Multi-objective optimisation
ISSN:0020-7543, 1366-588X
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Low costs, high reactivity and high quality products are necessary criteria for industries to achieve competitiveness in nowadays market. In this context, reconfigurable manufacturing systems (RMSs) have emerged to fulfil these requirements. RMS is one of the latest manufacturing paradigms, where machines components, software or material handling units can be added, removed, modified or interchanged as needed and when imposed by the necessity to react and respond rapidly and cost-effectively to changing. This research work addresses the multi-objective single-product multi-unit process plan generation problem in a reconfigurable manufacturing environment where three hybrid heuristics are proposed and compared namely: repetitive single-unit process plan heuristic (RSUPP), iterated local search on single-unit process plans heuristic (LSSUPP) and archive-based iterated local search heuristic (ABILS). Single-unit process plans are generated using the adapted non-dominated sorting genetic algorithm (NSGA-II). Moreover, in addition to the minimisation of the classical total production cost and the total completion time, the minimisation of the maximum machines exploitation time is considered as a novel optimisation criterion, in order to have high quality products. To illustrate the applicability of the three approaches, examples are presented and the obtained numerical results are analysed.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2019.1635277