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A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce

Author

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  • Bailing Liu
  • Hui Chen
  • Yanhui Li
  • Xiang Liu

Abstract

Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution system consisting of one supplier, a set of retailers, and a single type of product with continuous review ( Q, r ) inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability.

Suggested Citation

  • Bailing Liu & Hui Chen & Yanhui Li & Xiang Liu, 2015. "A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-15, March.
    • Handle: RePEc:hin:jnddns:586581
    DOI: 10.1155/2015/586581
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    Cited by:

    1. Straubert, Christian, 2024. "A continuous approximation location-inventory model with exact inventory costs and nonlinear delivery lead time penalties," International Journal of Production Economics, Elsevier, vol. 268(C).
    2. Cárdenas-Barrón, Leopoldo Eduardo & González-Velarde, José Luis & Treviño-Garza, Gerardo & Garza-Nuñez, Dagoberto, 2019. "Heuristic algorithm based on reduce and optimize approach for a selective and periodic inventory routing problem in a waste vegetable oil collection environment," International Journal of Production Economics, Elsevier, vol. 211(C), pages 44-59.
    3. Fathi, Mahdi & Khakifirooz, Marzieh & Diabat, Ali & Chen, Huangen, 2021. "An integrated queuing-stochastic optimization hybrid Genetic Algorithm for a location-inventory supply chain network," International Journal of Production Economics, Elsevier, vol. 237(C).
    4. Chávez, Marcela María Morales & Sarache, William & Costa, Yasel, 2018. "Towards a comprehensive model of a biofuel supply chain optimization from coffee crop residues," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 136-162.
    5. Lihua Liu & Lai Soon Lee & Hsin-Vonn Seow & Chuei Yee Chen, 2022. "Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method," Sustainability, MDPI, vol. 14(23), pages 1-39, November.
    6. Fokkema, Jan Eise & Land, Martin J. & Coelho, Leandro C. & Wortmann, Hans & Huitema, George B., 2020. "A continuous-time supply-driven inventory-constrained routing problem," Omega, Elsevier, vol. 92(C).
    7. Di Wu & Xuejun Ji & Fang Xiao & Shijie Sheng, 2022. "A Location Inventory Routing Optimisation Model and Algorithm for a Remote Island Shipping Network considering Emergency Inventory," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    8. Zhang, Jinchun & Lv, Hang & Hou, Jinxiu, 2023. "A novel general model for RAP and RRAP optimization of k-out-of-n:G systems with mixed redundancy strategy," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    9. Soysal, Mehmet & Koç, Çağrı & Çimen, Mustafa & İbiş, Merve, 2023. "Managing returnable transport items in a vendor managed inventory system," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).

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