Minimizing makespan wıth fuzzy processing times under job deterioration and learning effect

Oğuzhan Ahmet ARIK

This paper proposes a single machine/processor scheduling problem considering uncertain processing times under job deterioration and learning effect. In order to express uncertainty of parameters such as processing times, effects of deterioration and learning, fuzzy numbers are used. The objective function in this study is to minimize the makespan (maximum completion time) where the parameters of the problem are fully uncertain. In the literature, many single machine scheduling problems have been interested in deterministic model parameters such as processing times, due dates and release dates ...Daha fazlası

Makale/Derleme 2020 Journal of Industrial Engineering 6 Görüntülenme

A Genetic Algorithm Approach To Parallel Machine Scheduling Problems Under Effects Of Position-Dependent Learning And Linear Deterioration

Oğuzhan Ahmet ARIK

This paper investigates parallel machine scheduling problems where the objectives are to minimize total completion times under effects of learning and deterioration. The investigated problem is in NP-hard class and solution time for finding optimal solution is extremely high. The authors suggested a genetic algorithm, a well-known and strong metaheuristic algorithm, for the problem and we generated some test problems with learning and deterioration effects. The proposed genetic algorithm is compared with another existing metaheuristic for the problem. Experimental results show that the propose ...Daha fazlası

Makale/Derleme 2021 International Journal of Applied Metaheuristic Computing 7 Görüntülenme

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Minimizing makespan wıth fuzzy processing times under job deterioration and learning effect

Oğuzhan Ahmet ARIK

A Genetic Algorithm Approach To Parallel Machine Scheduling Problems Under Effects Of Position-Dependent Learning And Linear Deterioration

Oğuzhan Ahmet ARIK