Green mixed-model assembly lines sequencing problems

Document Type : Original Article

Author

Industrial Engineering Department, Faculty of basic science and Engineering, Kosar University of Bojnord,

Abstract

The focus of this paper is on sequencing problems in green MMALs with specific consideration to the line efficiency and the impact on the environment. By applying green supply chain management principles, we aim to minimize vehicle routes for product delivery and specifically reduce carbon dioxide emissions. The specific objectives of paper include to reduce total setup costs, minimize work overload situations, and lower total earliness and tardiness costs according to order priorities. To achieve these goals, we define a mathematical model and present new goals of sustainability. Because of the NP-hardness of this problem, we employ Benders decomposition to develop complex algorithms. The Benders decomposition algorithm is improved through incorporating acceleration techniques and adding optimality cuts. In addition, we use the Multi-objective Particle Swarm Optimization (MOPSO) algorithm for solving the proposed model and compare the results in view of different objectives. The comparison process demonstrates that the Benders decomposition with additional optimality cuts performs better than the MOPSO algorithm. The practical efficiency of the proposed Improved Benders Decomposition Algorithm (BDA) is proved with the experimental computations taking into consideration both small- and large-scale cases. On small-sized problems its algorithm obtains optimal solutions, and its improvement in objective function values is up to 3.9 percent with respect to the MOPSO algorithm, and its computing time used is also quite reasonable. Between the improved BDA and the MOPSO, the former was observed to have superior quality of solutions, both in actual solutions and in diversity measure, in large-scale test cases

Keywords

References

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Contributions of Science and Technology for Engineering
Volume 3, Issue 2
February 2026
Pages 51-70

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History

  • Receive Date: 27 April 2025
  • Revise Date: 12 July 2025
  • Accept Date: 17 August 2025
  • First Publish Date: 31 August 2025
  • Publish Date: 01 May 2026

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