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Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption

Author

Listed:
  • Ieva Meidute-Kavaliauskiene

    (Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Sauletekio al. 11, 10223 Vilnius, Lithuania)

  • Nihal Sütütemiz

    (Department of Management Information Systems, University of Sakarya, Sakarya 54050, Turkey)

  • Figen Yıldırım

    (Department of International Trade, Istanbul Commerce University, Istambul 34445, Turkey)

  • Shahryar Ghorbani

    (Department of Production Management, University of Sakarya, Sakarya 54050, Turkey)

  • Renata Činčikaitė

    (Department of Business Technologies and Entrepreneurship, Vilnius Gediminas Technical University, Sauletekio al. 11, 10223 Vilnius, Lithuania)

Abstract

Cross-docking is an excellent way to reduce the space required to store goods, inventory management costs, and customer order delivery time. This paper focuses on cost optimization, scheduling incoming and outgoing trucks, and green supply chains with multiple cross-docking. The three objectives are minimizing total operating costs, truck transportation sequences, and carbon emissions within the supply chain. Since the linear programming model is an integer of zero and one and belongs to NP-hard problems, its solution time increases sharply with increasing dimensions. Therefore, the non-dominated sorting genetic algorithm-II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) were used to find near-optimal solutions to the problem. Then, these algorithms were compared with criteria such as execution time and distance from the ideal point, and the superior algorithm in each criterion was identified.

Suggested Citation

  • Ieva Meidute-Kavaliauskiene & Nihal Sütütemiz & Figen Yıldırım & Shahryar Ghorbani & Renata Činčikaitė, 2022. "Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption," Energies, MDPI, vol. 15(4), pages 1-24, February.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:4:p:1530-:d:753058
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    References listed on IDEAS

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    Cited by:

    1. Ratko Stanković & Kristijan Rogić & Mario Šafran, 2022. "Saving Energy by Optimizing Warehouse Dock Door Allocation," Energies, MDPI, vol. 15(16), pages 1-14, August.
    2. Liudmyla Davydenko & Nina Davydenko & Andrii Bosak & Alla Bosak & Agnieszka Deja & Tygran Dzhuguryan, 2022. "Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging," Energies, MDPI, vol. 15(10), pages 1-27, May.

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