Publication:
Solving the unrelated parallel batch machine scheduling problem with mixed-integer programming

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Date

2021-12-31

Authors

Bakir, Merve
Sebatli-Saglam, Asli
Cavdur, Fatih

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Gazi Üniversitesi

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Abstract

In this study, the problem of scheduling jobs with arbitrary sizes and non-zero release times on a set of unrelated parallel batch processing machines with different capacities is discussed. Three mixed-integer programming models with different objective functions are developed to solve the problem. Corresponding models aim at minimizing (i) the total flow time, (ii) the makespan and (iii) the total tardiness, respectively, which are considered to be among the most important objectives in scheduling problems. In order to test the validity and applicability of the proposed solution approach, different datasets are generated using some rules in the literature. The results obtained by solving the mathematical programming models with these data sets are analyzed in terms of some performance parameters.

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Keywords

Iterated greedy algorithm, Nonidentical job sizes, Total flow time, Processing machines, Minimizing makespan, Weighted-tardiness, Release times, Minimization, Capacities, Earliness, Unrelated parallel batch processing, Machine scheduling, Total flow time, Makespan, Total tardiness, Mixed-integer programming, Science & technology, Technology, Engineering, multidisciplinary, Engineering

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