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    An energy-efficient permutation flowshop scheduling problem
    (Pergamon-Elsevier Science Ltd, 2020) Öztop, Hande; Taşgetiren, M. Fatih; Eliiyi, Deniz Türsel; Pan, Quan-Ke; Kandiller, Levent
    The permutation flowshop scheduling problem (PFSP) has been extensively explored in scheduling literature because it has many real-world industrial implementations. In some studies, multiple objectives related to production efficiency have been considered simultaneously. However, studies that consider energy consumption and environmental impacts are very rare in a multi-objective setting. In this work, we studied two contradictory objectives, namely, total flowtime and total energy consumption (TEC) in a green permutation flowshop environment, in which the machines can be operated at varying speed levels corresponding to different energy consumption values. A bi-objective mixed-integer programming model formulation was developed for the problem using a speed-scaling framework. To address the conflicting objectives of minimizing TEC and total flowtime, the augmented epsilon-constraint approach was employed to obtain Pareto-optimal solutions. We obtained near approximations for the Pareto-optimal frontiers of small-scale problems using a very small epsilon level. Furthermore, the mathematical model was run with a time limit to find sets of non-dominated solutions for large instances. As the problem was NP-hard, two effective multi-objective iterated greedy algorithms and a multi-objective variable block insertion heuristic were also proposed for the problem as well as a novel construction heuristic for initial solution generation. The performance of the developed heuristic algorithms was assessed on well-known benchmark problems in terms of various quality measures. Initially, the performance of the algorithms was evaluated on small-scale instances using Pareto-optimal solutions. Then, it was shown that the developed algorithms are tremendously effective for solving large instances in comparison to time-limited model. (C) 2020 Elsevier Ltd. All rights reserved.
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    Metaheuristic algorithms for the hybrid flowshop scheduling problem
    (Pergamon-Elsevier Science Ltd, 2019) Öztop, Hande; Taşgetiren, M. Fatih; Eliiyi, Deniz Türsel; Pan, Quan-Ke
    The hybrid flowshop scheduling problem (HFSP) has been widely studied in the literature, as it has many real-life applications in industry. Even though many solution approaches have been presented for the HFSP with makespan criterion, studies on HFSP with total flow time minimization have been rather limited. This study presents a mathematical model, four variants of iterated greedy algorithms and a variable block insertion heuristic for the HFSP with total flow time minimization. Based on the well-known NEH heuristic, an efficient constructive heuristic is also proposed, and compared with NEH. A detailed design of experiment is carried out to calibrate the parameters of the proposed algorithms. The HFSP benchmark suite is used for evaluating the performance of the proposed methods. As there are only 10 large instances in the current literature, further 30 large instances are proposed as new benchmarks. The developed model is solved for all instances on CPLEX under a time limit, and the performances of the proposed algorithms are assessed through comparisons with the results from CPLEX and the two best-performing algorithms in literature. Computational results show that the proposed algorithms are very effective in terms of solution time and quality. Additionally, the proposed algorithms are tested on large instances for the makespan criterion, which reveal that they also perform superbly for the makespan objective. Especially for instances with 30 jobs, the proposed algorithms are able to find the current incumbent makespan values reported in literature, and provide three new best solutions. (C) 2019 Elsevier Ltd. All rights reserved.