IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v204y2025ics1366554525004946.html

Multi-objective double-floor corridor allocation problem with floor loads and separated passages

Author

Listed:
  • Ji, Dan
  • Zhang, Zeqiang
  • Liang, Wei
  • Guo, Zihan
  • He, Zongxing

Abstract

Current research on multi-floor stereoscopic workshop layouts disregards the effects of floor load constraints and interference with the workers and logistics, which lead to low productivity and escalating transportation risks. This study examines a double-floor corridor allocation problem considering floor loads and separated worker-logistics transportation passages (DFCAP_FLSP). To this end, a mixed-integer programming model involving constraints on facility allocation, multi-type transportation distance computation, and floor loading is constructed to minimize material handling costs, employee walking distances, and floor loading gaps. Subsequently, a multi-objective self-learning memetic algorithm (MOSLMA) is developed to solve the DFCAP_FLSP efficiently. The algorithm employs linear programming to achieve two-stage decoding and utilizes Q-learning to improve local search performance. Comparison experiments conducted with the genetic algorithm, multi-objective particle swarm optimization, and non-dominated sorting genetic algorithm II for the four benchmark instances reveal that MOSLMA achieved the highest percentages of non-inferior solutions close to the Pareto solution (68.75%, 93.18%, 100%, and 87.5%), highlighting its advantages. Finally, the proposed layout and algorithm are applied to the reducer manufacturing workshop, and the scheme comparison indicates the superiority of the proposed layout structure in safety and cost-effectiveness.

Suggested Citation

  • Ji, Dan & Zhang, Zeqiang & Liang, Wei & Guo, Zihan & He, Zongxing, 2025. "Multi-objective double-floor corridor allocation problem with floor loads and separated passages," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:transe:v:204:y:2025:i:c:s1366554525004946
    DOI: 10.1016/j.tre.2025.104453
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554525004946
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tre.2025.104453?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Liu, Yubin & Ye, Qiming & Escribano-Macias, Jose & Feng, Yuxiang & Candela, Eduardo & Angeloudis, Panagiotis, 2023. "Route planning for last-mile deliveries using mobile parcel lockers: A hybrid q-learning network approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    2. Wang, Peixiang & Xu, Qihang & Li, Yufei & Chen, Qunlong & Tao, Jinghan & Qin, Wei & Huang, Heng & Zou, Ying, 2025. "Learning-based hybrid algorithms for container relocation problem with storage plan," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 197(C).
    3. Pablo Pérez-Gosende & Josefa Mula & Manuel Díaz-Madroñero, 2021. "Facility layout planning. An extended literature review," International Journal of Production Research, Taylor & Francis Journals, vol. 59(12), pages 3777-3816, June.
    4. Wanying Amanda Chen & René de Koster & Yeming Gong, 2023. "Warehouses without aisles : Layout design of a multi-deep rack climbing robotic system," Post-Print hal-04343870, HAL.
    5. Shi, Ziyi & Xu, Meng & Song, Yancun & Zhu, Zheng, 2024. "Multi-Platform dynamic game and operation of hybrid Bike-Sharing systems based on reinforcement learning," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 181(C).
    6. Yong Jin Suh & Jin Young Choi, 2022. "Efficient Fab facility layout with spine structure using genetic algorithm under various material-handling considerations," International Journal of Production Research, Taylor & Francis Journals, vol. 60(9), pages 2816-2829, May.
    7. Tronconi, Riccardo & Pilati, Francesco, 2025. "Social, economic and green optimization of the distribution process of e-commerce platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 196(C).
    8. Shen, Liang & Xu, Xiang & Shao, Feng & Shao, Hu & Ge, Yanxin, 2024. "A multi-objective optimization model for medical waste recycling network design under uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    9. Palubeckis, Gintaras, 2025. "A fast local search based memetic algorithm for the parallel row ordering problem," Applied Mathematics and Computation, Elsevier, vol. 486(C).
    10. Donald M. Simmons, 1969. "One-Dimensional Space Allocation: An Ordering Algorithm," Operations Research, INFORMS, vol. 17(5), pages 812-826, October.
    11. Ahonen, H. & de Alvarenga, A.G. & Amaral, A.R.S., 2014. "Simulated annealing and tabu search approaches for the Corridor Allocation Problem," European Journal of Operational Research, Elsevier, vol. 232(1), pages 221-233.
    12. Junqi Liu & Zeqiang Zhang & Feng Chen & Silu Liu & Lixia Zhu, 2022. "A novel hybrid immune clonal selection algorithm for the constrained corridor allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 953-972, April.
    13. Ghosh, Diptesh & Kothari, Ravi, 2012. "Population Heuristics for the Corridor Allocation Problem," IIMA Working Papers WP2012-09-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    14. Pang, Xinfu & Wang, Yibao & Yu, Yang & Liu, Wei, 2024. "Optimal scheduling of a cogeneration system via Q-learning-based memetic algorithm considering demand-side response," Energy, Elsevier, vol. 300(C).
    15. Chao Guan & Zeqiang Zhang & Yunpeng Li, 2019. "A flower pollination algorithm for the double-floor corridor allocation problem," International Journal of Production Research, Taylor & Francis Journals, vol. 57(20), pages 6506-6527, October.
    16. Li, Kunpeng & Liu, Tengbo & Ram Kumar, P.N. & Han, Xuefang, 2024. "A reinforcement learning-based hyper-heuristic for AGV task assignment and route planning in parts-to-picker warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    17. Chen, Wanying (Amanda) & De Koster, René & Gong, Yeming, 2023. "Warehouses without aisles: Layout design of a multi-deep rack climbing robotic system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    18. Tian, Ran & Chang, Longlong & Sun, Zhihui & Zhao, Guanglu & Lu, Xin, 2025. "PTB: A deep reinforcement learning method for flexible logistics service combination problem with spatial-temporal constraint," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 195(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Junqi Liu & Zeqiang Zhang & Feng Chen & Silu Liu & Lixia Zhu, 2022. "A novel hybrid immune clonal selection algorithm for the constrained corridor allocation problem," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 953-972, April.
    2. Dahlbeck, Mirko & Fischer, Anja & Fischer, Frank & Hungerländer, Philipp & Maier, Kerstin, 2023. "Exact approaches for the combined cell layout problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 530-546.
    3. Zhang, Zhengmin & Gong, Yeming & Yuan, Zhe & Chen, Wanying, 2024. "Robotic warehouse systems considering dynamic priority," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    4. Palubeckis, Gintaras, 2025. "A fast local search based memetic algorithm for the parallel row ordering problem," Applied Mathematics and Computation, Elsevier, vol. 486(C).
    5. Herrán, Alberto & Manuel Colmenar, J. & Duarte, Abraham, 2021. "An efficient variable neighborhood search for the Space-Free Multi-Row Facility Layout problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 893-907.
    6. Ma, Benedict Jun & Pan, Shenle & Zou, Bipan & Kuo, Yong-Hong & Huang, George Q., 2025. "Operating policies for robotic cellular warehousing systems," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    7. Anjos, Miguel F. & Vieira, Manuel V.C., 2017. "Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions," European Journal of Operational Research, Elsevier, vol. 261(1), pages 1-16.
    8. Dahlbeck, Mirko & Fischer, Anja & Fischer, Frank, 2020. "Decorous combinatorial lower bounds for row layout problems," European Journal of Operational Research, Elsevier, vol. 286(3), pages 929-944.
    9. Zhao, Zheng & Cheng, Junkai & Zhao, Jianyi & Zhen, Lu, 2025. "Column generation for scheduling mobile composite robots in warehouses," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 194(C).
    10. Ahonen, H. & de Alvarenga, A.G. & Amaral, A.R.S., 2014. "Simulated annealing and tabu search approaches for the Corridor Allocation Problem," European Journal of Operational Research, Elsevier, vol. 232(1), pages 221-233.
    11. A. R. S. Amaral, 2022. "A heuristic approach for the double row layout problem," Annals of Operations Research, Springer, vol. 316(2), pages 1-36, September.
    12. Chen, Wanying & Jiang, Binglei & Wang, Jie & Zhou, Jingjing, 2026. "Impact of modular design: Performance evaluation and operating policies of a modular robotic compact storage and retrieval system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 206(C).
    13. Wu, Song & Yang, Wei & Hanafi, Saïd & Wilbaut, Christophe & Wang, Yang, 2024. "Iterated local search with ejection chains for the space-free multi-row facility layout problem," European Journal of Operational Research, Elsevier, vol. 316(3), pages 873-886.
    14. Benjamin Heinbach & Peter Burggräf & Johannes Wagner, 2024. "gym-flp: A Python Package for Training Reinforcement Learning Algorithms on Facility Layout Problems," SN Operations Research Forum, Springer, vol. 5(1), pages 1-26, March.
    15. Dayal, Eshwar & Khuntia, Lisa & Lakshay, Lakshay & Buldeo Rai, Heleen & Pani, Agnivesh, 2025. "Behavioral intention to use parcel lockers in the last mile and underlying linkages with travel modal choice," Research in Transportation Economics, Elsevier, vol. 111(C).
    16. Chen, Enming & Zhou, Zhongbao & Li, Ruiyang & Chang, Zhongxiang & Shi, Jianmai, 2024. "The multi-fleet delivery problem combined with trucks, tricycles, and drones for last-mile logistics efficiency requirements under multiple budget constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 187(C).
    17. Daria Leiber & David Eickholt & Anh-Tu Vuong & Gunther Reinhart, 2022. "Simulation-based layout optimization for multi-station assembly lines," Journal of Intelligent Manufacturing, Springer, vol. 33(2), pages 537-554, February.
    18. Uma Kothari & Diptesh Ghosh, 2012. "A Competitive Genetic Algorithm for Single Row Facility Layout," Working Papers id:4915, eSocialSciences.
    19. Sina Mohri, Seyed & Ghaderi, Hadi & Van Woensel, Tom & Mohammadi, Mehrdad & Nassir, Neema & Thompson, Russell G., 2024. "Contextualizing alternative delivery points in last mile delivery," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    20. Ghosh, Diptesh & Kothari, Ravi, 2012. "Population Heuristics for the Corridor Allocation Problem," IIMA Working Papers WP2012-09-02, Indian Institute of Management Ahmedabad, Research and Publication Department.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:204:y:2025:i:c:s1366554525004946. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.