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Location-Routing Optimization for Two-Echelon Cold Chain Logistics of Front Warehouses Based on a Hybrid Ant Colony Algorithm

Author

Listed:
  • Xuya Zhang

    (College of Information Management, Nanjing Agricultural University, Nanjing 210031, China)

  • Yue Wang

    (College of Information Management, Nanjing Agricultural University, Nanjing 210031, China)

  • Dongqing Zhang

    (College of Information Management, Nanjing Agricultural University, Nanjing 210031, China)

Abstract

Diverse demands have promoted the rapid development of the cold chain logistics industry. In the paper, a novel approach for calculating the comprehensive carbon emission cost was proposed and the front warehouse mode was analyzed under the background of energy conservation and emission reduction. To solve the two-echelon low-carbon location-routing problem (2E-LCLRP), a mathematical model considering operating cost, total transportation cost, fixed cost, refrigeration cost, cargo damage cost, and comprehensive carbon emission cost was proposed to determine the minimum total cost. A hybrid ant colony optimization (HACO) algorithm based on an elbow rule and an improved ant colony optimization (IACO) algorithm was proposed to solve the 2E-LCLRP. According to the elbow rule, the optimal number of front warehouses was determined and an IACO algorithm was then designed to optimize vehicle routes. An adaptive hybrid selection strategy and an optimized pheromone update mechanism were integrated into the HACO algorithm to accelerate convergence and obtain global optimal solutions. The proposed model and algorithm were verified through the case study of the 2E-LCLRP in Nanjing, China. The HACO algorithm outperformed the original ant colony optimization (ACO) algorithm in terms of convergence rate and solution quality. This study provides significant insights for enhancing heuristic algorithms as well as valuable research methods. Furthermore, the results can help cold chain logistics companies in balancing economic costs and environmental benefits and address cold chain distribution of agricultural products.

Suggested Citation

  • Xuya Zhang & Yue Wang & Dongqing Zhang, 2024. "Location-Routing Optimization for Two-Echelon Cold Chain Logistics of Front Warehouses Based on a Hybrid Ant Colony Algorithm," Mathematics, MDPI, vol. 12(12), pages 1-22, June.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:12:p:1851-:d:1414650
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    References listed on IDEAS

    as
    1. Chungmok Lee, 2021. "An exact algorithm for the electric-vehicle routing problem with nonlinear charging time," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(7), pages 1461-1485, July.
    2. Nilsson, Måns & Nykvist, Björn, 2016. "Governing the electric vehicle transition – Near term interventions to support a green energy economy," Applied Energy, Elsevier, vol. 179(C), pages 1360-1371.
    3. Jing Chen & Pengfei Gui & Tao Ding & Sanggyun Na & Yingtang Zhou, 2019. "Optimization of Transportation Routing Problem for Fresh Food by Improved Ant Colony Algorithm Based on Tabu Search," Sustainability, MDPI, vol. 11(23), pages 1-22, November.
    4. Shengbin Liang & Tongtong Jiao & Wencai Du & Shenming Qu, 2021. "An improved ant colony optimization algorithm based on context for tourism route planning," PLOS ONE, Public Library of Science, vol. 16(9), pages 1-16, September.
    5. Songyi Wang & Fengming Tao & Yuhe Shi, 2018. "Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint," IJERPH, MDPI, vol. 15(1), pages 1-17, January.
    6. Darvish, Maryam & Archetti, Claudia & Coelho, Leandro C. & Speranza, M. Grazia, 2019. "Flexible two-echelon location routing problem," European Journal of Operational Research, Elsevier, vol. 277(3), pages 1124-1136.
    7. Henryk Dzwigol & Nataliia Trushkina & Aleksy Kwilinski, 2021. "The Organizational and Economic Mechanism of Implementing the Concept of Green Logistics," Virtual Economics, The London Academy of Science and Business, vol. 4(2), pages 41-75, April.
    8. Christensen, Tue Rauff Lind & Klose, Andreas, 2021. "A fast exact method for the capacitated facility location problem with differentiable convex production costs," European Journal of Operational Research, Elsevier, vol. 292(3), pages 855-868.
    9. Liu, Zheng & Huang, Yu-Qing & Shang, Wen-Long & Zhao, Yuan-Jun & Yang, Zao-Li & Zhao, Zhao, 2022. "Precooling energy and carbon emission reduction technology investment model in a fresh food cold chain based on a differential game," Applied Energy, Elsevier, vol. 326(C).
    10. Wang, Yong & Peng, Shouguo & Zhou, Xuesong & Mahmoudi, Monirehalsadat & Zhen, Lu, 2020. "Green logistics location-routing problem with eco-packages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    11. Fangfang Zheng & Xiaofang Meng & Lidi Wang & Nannan Zhang, 2023. "Operation Optimization Method of Distribution Network with Wind Turbine and Photovoltaic Considering Clustering and Energy Storage," Sustainability, MDPI, vol. 15(3), pages 1-22, January.
    12. Okan Arslan & Oya Ekin Karaşan & Ridha Mahjoub & Hande Yaman, 2019. "A Branch-and-Cut Algorithm for the Alternative Fuel Refueling Station Location Problem with Routing," Transportation Science, INFORMS, vol. 53(4), pages 1107-1125, July.
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