Low Carbon Emissions in Flow Shop Group Scheduling under Learning Effect Consideration

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Djazia Nadjat Sekkal
Fayçal Belkaid
Elouchdi Mouna

Abstract

This paper deals with a flow shop group problem with sequence dependent setup time and learning effect. A mixed integer linear programming model is proposed for the minimization of total tardiness as an indicator of punctuality and efficiency in a just-in-time production, and the minimization of carbon emissions as an ecological indicator in an environmental preservation perspective. The mathematical model is efficient but cannot solve the problem when the size of the instances increases, therefore the multi-objective simulated annealing metaheuristic MOSA is proposed to tackle the studied problem. Several experiments are conducted in which the coefficients of the two objective functions and the learning rate are varied. Through the obtained results, the efficiency of the algorithm is highlighted and demonstrated.

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How to Cite
Djazia Nadjat Sekkal, Fayçal Belkaid, & Elouchdi Mouna. (2022). Low Carbon Emissions in Flow Shop Group Scheduling under Learning Effect Consideration. European Economic Letters (EEL), 12(2), 26–37. https://doi.org/10.52783/eel.v12i2.90
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