An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints

Min Dai, Ziwei Zhang, Adriana Giret and Miguel A. Salido
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Min Dai: College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China
Ziwei Zhang: College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China
Adriana Giret: Departamento de Sistemas Informáticos y Computación/AI2, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
Miguel A. Salido: Departamento de Sistemas Informáticos y Computación/AI2, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain

Sustainability, 2019, vol. 11, issue 11, 1-23

Abstract: Nowadays, the manufacturing industry faces the challenge of reducing energy consumption and the associated environmental impacts. Production scheduling is an effective approach for energy-savings management. During the entire workshop production process, both the processing and transportation operations consume large amounts of energy. To reduce energy consumption, an energy-efficient job-shop scheduling problem (EJSP) with transportation constraints was proposed in this paper. First, a mixed-integer programming model was established to minimize both the comprehensive energy consumption and makespan in the EJSP. Then, an enhanced estimation of distribution algorithm (EEDA) was developed to solve the problem. In the proposed algorithm, an estimation of distribution algorithm was employed to perform the global search and an improved simulated annealing algorithm was designed to perform the local search. Finally, numerical experiments were implemented to analyze the performance of the EEDA. The results showed that the EEDA is a promising approach and that it can solve EJSP effectively and efficiently.

Keywords: job-shop scheduling; energy consumption; estimation of distribution algorithm; transportation time (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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