Ensemble of metaheuristics for energy-efficient hybrid flowshops: Makespan versus total energy consumption
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Tarih
2020
Dergi Başlığı
Dergi ISSN
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Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Due to its practical relevance, the hybrid flowshop scheduling problem (HFSP) has been widely studied in the literature with the objectives related to production efficiency. However, studies regarding energy consumption and environmental effects have rather been limited. This paper addresses the trade-off between makespan and total energy consumption in hybrid flowshops, where machines can operate a varying speed levels. A bi-objective mixed-integer linear programming (MILP) model and a bi-objective constraint programming (CP) model are proposed for the problem employing speed scaling. Since the objectives of minimizing makespan and total energy consumption are conflicting with each other, the augmented epsilon (epsilon)-constraint approach is used for obtaining the Pareto-optimal solutions. While close approximations for the Pareto-optimal frontier are obtained for small-sized instances, sets of non-dominated solutions are obtained for large instances by solving the MILP and CP models under a time limit. As the problem is NP-hard, two variants of the iterated greedy algorithm, a variable block insertion heuristic and four variants of ensemble of metaheuristic algorithms are also proposed, as well as a novel constructive heuristic. The performances of the proposed seven bi-objective metaheuristics are compared with each other as well as the MILP and CP solutions on a set of well-known HFSP benchmarks in terms of cardinality, closeness, and diversity of the solutions. Initially, the performances of the algorithms are tested on small-sized instances with respect to the Pareto-optimal solutions. Then, it is shown that the proposed algorithms are very effective for solving large instances in terms of both solution quality and CPU time.
Açıklama
Anahtar Kelimeler
Hybrid flowshop scheduling, Energy-efficient scheduling, Multi-objective optimization, Metaheuristics, Shop Scheduling Problem, Multiobjective Genetic Algorithm, Differential Evolution Algorithm, Iterated Greedy Algorithm, Total Weighted Tardiness, Power-Consumption, Optimization Algorithm, Local Search, Flow Shops, Machine
