Abstract:In this paper we propose to solve a single machine scheduling problem which has to undergo a periodic preventive maintenance. The objective is to minimize the weighted sum of the completion times. This criterion is defined as one of the most important objectives in practice but has not been studied so far for the considered problem. As the problem is proven to be NP-hard, and a mathematical model is proposed in the literature, we propose to use General Variable Neighborhood Search algorithm to solve this probl… Show more
“…(2018, 2019), Huo and Zhao (2018), Kaabi (2019), Krim et al. (2019a, 2019b, 2020), Luo and Liu (2017), Najat et al. (2019), Shen and Zhu (2018), Touat et al.…”
Traditional scheduling assumes that production can continue around the clock unless machines are not available. This is not without question for labor-intensive industries where operations are performed manually. Motivated by operation management problems arising in the assembly stage of aeroengines and in the paintspraying stage of wooden furniture, we consider a scheduling problem with day shifts and breaks. We transform the problem into a new bin-packing problem and present some theoretical analyses. To meet the needs of practical applications, we propose a binary integer programming (BIP) formulation and a hybrid genetic algorithm (HGA) that is based on five heuristic algorithms and two postoptimization procedures. Computational results indicate that the BIP formulation is suitable for some data sets while the HGA is the most promising in that it saves about 37% of day shifts compared to the best of the five heuristic algorithms in the context of scheduling.
“…(2018, 2019), Huo and Zhao (2018), Kaabi (2019), Krim et al. (2019a, 2019b, 2020), Luo and Liu (2017), Najat et al. (2019), Shen and Zhu (2018), Touat et al.…”
Traditional scheduling assumes that production can continue around the clock unless machines are not available. This is not without question for labor-intensive industries where operations are performed manually. Motivated by operation management problems arising in the assembly stage of aeroengines and in the paintspraying stage of wooden furniture, we consider a scheduling problem with day shifts and breaks. We transform the problem into a new bin-packing problem and present some theoretical analyses. To meet the needs of practical applications, we propose a binary integer programming (BIP) formulation and a hybrid genetic algorithm (HGA) that is based on five heuristic algorithms and two postoptimization procedures. Computational results indicate that the BIP formulation is suitable for some data sets while the HGA is the most promising in that it saves about 37% of day shifts compared to the best of the five heuristic algorithms in the context of scheduling.
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