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A Genetic algorithm with shuffle to solve the job shop scheduling problem
Högskolan Väst, Institutionen för ingenjörsvetenskap, Avd för automationssystem.
2015 (engelsk)Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
Abstract [en]

Job shop scheduling problems are computationally complex combinatorial optimization problems. Genetic algorithms have been used in various forms and in combination with other algorithms to solve job shop scheduling problems. A partially flexible job shop with precedence constraints increases this complex behaviour. There are two main parts to optimizing a job shop, the routing and the scheduling. The objective here is to get consistent optimal makespan using a genetic algorithm. This paper firstly, presents a representation of the considered partially flexible job shop scheduling problem, which helps take into account the precedence constraints and reduce situations of deadlock. It starts with the genetic crossovers for routing and then a random shuffle technique is used for scheduling the problem. The computational results have shown that the algorithm performs well in terms of finding a consistent optimal schedule for the given problem.

sted, utgiver, år, opplag, sider
2015. , s. 14
Emneord [en]
Job shop scheduling, genetic algorithm, shuffle, string, makespan
HSV kategori
Identifikatorer
URN: urn:nbn:se:hv:diva-9011Lokal ID: EXR900OAI: oai:DiVA.org:hv-9011DiVA, id: diva2:900850
Fag / kurs
Mechanical engineering
Utdanningsprogram
Robotteknik
Veileder
Examiner
Tilgjengelig fra: 2016-02-06 Laget: 2016-02-05 Sist oppdatert: 2016-02-06bibliografisk kontrollert

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Totalt: 331 treff
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