Next Article in Journal
Environmentalism and Polish Coal Mining: A Multilevel Study
Next Article in Special Issue
Multi-Objective Sustainable Truck Scheduling in a Rail–Road Physical Internet Cross-Docking Hub Considering Energy Consumption
Previous Article in Journal
Human and Natural Impacts on the Water Resources in the Syr Darya River Basin, Central Asia
Previous Article in Special Issue
A Novel Reverse Logistics Network Design Considering Multi-Level Investments for Facility Reconstruction with Environmental Considerations
Article Menu
Issue 11 (June-1) cover image

Export Article

Open AccessArticle

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

1
College of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China
2
Departamento de Sistemas Informáticos y Computación/AI2, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2019, 11(11), 3085; https://doi.org/10.3390/su11113085
Received: 30 April 2019 / Revised: 29 May 2019 / Accepted: 29 May 2019 / Published: 31 May 2019
(This article belongs to the Special Issue Sustainable Intelligent Manufacturing Systems)
  |  
PDF [1737 KB, uploaded 4 June 2019]
  |  

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. View Full-Text
Keywords: job-shop scheduling; energy consumption; estimation of distribution algorithm; transportation time job-shop scheduling; energy consumption; estimation of distribution algorithm; transportation time
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Dai, M.; Zhang, Z.; Giret, A.; Salido, M.A. An Enhanced Estimation of Distribution Algorithm for Energy-Efficient Job-Shop Scheduling Problems with Transportation Constraints. Sustainability 2019, 11, 3085.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sustainability EISSN 2071-1050 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top