Fatemeh Ganji; Amir Jamali
Abstract
In this study, single machine scheduling with flexible maintenance is investigated with non-resumable jobs by minimizing the weighted number of tardy jobs. It is assumed that the machine stops for a constant interval time during the scheduling period to perform maintenance. In other words, the starting ...
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In this study, single machine scheduling with flexible maintenance is investigated with non-resumable jobs by minimizing the weighted number of tardy jobs. It is assumed that the machine stops for a constant interval time during the scheduling period to perform maintenance. In other words, the starting time of maintenance is the decision variable. By reviewing the literature, we noticed that this problem has not been studied yet. Initially, it is proved that the problem is NP-hard. Then, a mathematical model is proposed and solved by the GAMS software. Because of the long time for solving the problem with an exact method, we develop a heuristic algorithm. To evaluate the efficiency of the proposed algorithm, 696 test problems with different sizes of the problem in the range from 1 to 2000 jobs, are generated. The computational results demonstrate that the average error of solution is 10.93\%.
Reza Baradaran Kazemzadeh; Seyyed Hesamoddin Zegardi; Mohammad Ali Beheshti Nia
Abstract
This study considers scheduling in Hybrid flow shop environment with unrelated parallel machines for minimizing mean of job's tardiness and mean of job's completion times. This problem does not study in the literature, so far. Flexible flow shop environment is applicable in various industries such as ...
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This study considers scheduling in Hybrid flow shop environment with unrelated parallel machines for minimizing mean of job's tardiness and mean of job's completion times. This problem does not study in the literature, so far. Flexible flow shop environment is applicable in various industries such as wire and spring manufacturing, electronic industries and production lines. After modeling the problem as a mixed integer programming model, three heuristics named Cluster, H1 and H2 is proposed for solving it. The first heuristic (Cluster) algorithm utilizes clustering methods for determining sequence of jobs. The second and third heuristics (H1 and H2) determine sequence of jobs with using SPT and EDD rules, respectively. The experimental results of study show that Cluster algorithm outperforms H1 and H2.