A Steady-State Genetic Algorithm for the Single Machine Scheduling Problem with Periodic Machine Availability

This paper presents an evolutionary algorithm-based steady-state grouping genetic algorithm (SSGGA) for the single-machine scheduling problem with periodic machine availability (SinMSPMA problem) whose objective is to minimize the makespan. This problem is N P -hard which arises in several real prod...

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Vydáno v:	SN computer science Ročník 4; číslo 5; s. 651
Hlavní autoři:	Chaubey, Punit Kumar, Sundar, Shyam
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Singapore Springer Nature Singapore 01.09.2023 Springer Nature B.V
Témata:	Availability Computer Imaging Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Evolutionary algorithms Genetic algorithms Heuristic Information Systems and Communication Service Integer programming Linear programming Machinery Original Research Packing problem Pattern Recognition and Graphics Production scheduling Research Trends in Computational Intelligence Scheduling Software Engineering/Programming and Operating Systems Steady state Vision Production scheduling Makespan Steady-state genetic algorithm Evolutionary algorithm
ISSN:	2661-8907, 2662-995X, 2661-8907
On-line přístup:	Získat plný text
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