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Floyd-Warshall ve Karınca Kolonisi Optimizasyonu Algoritmaları ile Depo Rota Planlaması

Year 2025, Volume: 59 Issue: 2, 335 - 352, 16.04.2025

Furkan Ulu , Gülveren Tabansız Göç , Fatih Çavdur

https://doi.org/10.51551/verimlilik.1539618

Abstract

Amaç: Bu çalışmada, depo rota planlama problemleri için tam ve bütünleşik bir çözüm yaklaşımı önerilmektedir.
Yöntem: Önerilen çözüm yaklaşımına göre, öncelikle depoda ziyaret edilmesi gereken noktaların bazılarını temsil eden bir ağ gösterimi oluşturulmaktadır. Daha sonra, her turda bir gezgin satıcı problemi oluşturmak ve söz konusu ağ yapısının ilgili düğümler arasındaki en kısa yolların belirlenmesi için Floyd-Warshall algoritması kullanılmaktadır. Son olarak, aracın toplam seyahat mesafesini minimize ederek ilgili gezgin satıcı probleminin çözümünü sağlamak için karınca kolonisi optimizasyonu algoritması kullanılmaktadır.
Bulgular: Önerilen çözüm yaklaşımının performansını göstermek için çeşitli veri kümeleri ile hesaplamalı deneyler gerçekleştirilmiştir. Sonuçların oldukça tatmin edici olduğu ve önerilen çözüm metodolojisinin depo rota planlamasında önemli faydalar sağlayabileceği gözlemlenmiştir.
Özgünlük: Çalışmanın en önemli katkısını, depo rota planlama problemi için Floyd-Warshall algoritması ile karınca kolonisi optimizasyonu algoritmasını bir arada kullanan esnek bir çözüm yaklaşımı çerçevesi sunulması oluşturmaktadır.

Keywords

En Kısa Yol Problemi Gezgin Satıcı Problemi (GSP) Floyd-Warshall Algoritması Karınca Kolonisi Optimizasyonu (KKO) Algoritması Rota Planlama

Supporting Institution

TÜBİTAK

Thanks

Bu çalışmada süresince, Yazar 2'ye sağlanan destekler için TÜBİTAK'a teşekkür ederiz.

References

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Warehouse Route Planning via Floyd-Warshall and Ant Colony Optimization Algorithms

Year 2025, Volume: 59 Issue: 2, 335 - 352, 16.04.2025

Furkan Ulu , Gülveren Tabansız Göç , Fatih Çavdur

https://doi.org/10.51551/verimlilik.1539618

Abstract

Purpose: In this study, we propose a complete and integrated solution approach for warehouse route planning problems.
Methodology: According to the proposed solution approach, a graph representation of the warehouse is first constructed where some vertices correspond to points to be visited. The Floyd-Warshall algorithm is employed to calculate the shortest paths between the corresponding points of the graph to formulate a traveling salesman problem for each tour. Finally, the ant colony optimization algorithm is utilized to solve the corresponding traveling salesman problem by minimizing the total travel distance.
Findings: Computational experiments are conducted with different datasets to demonstrate the performance of the proposed solution approach. It is observed that the results are quite satisfactory and the proposed solution methodology might provide significant benefits in warehouse route planning.
Originality: The main important contribution of our study is the proposal of a flexible solution framework that combines the Floyd-Warshall algorithm and the ant colony optimization algorithm for the general route planning problem.

Keywords

Shortest Path Problem Traveling Salesman Problem (TSP) Floyd-Warshall Algorithm Ant Colony Optimization (ACO) Algorithm Route Planning

Supporting Institution

TUBITAK

Thanks

We would like to thank TUBITAK for the supports provided to Author 2 during this study.

References

  • Aerts, B., Cornelissens, T. ve Sörensen, K. (2021). “The Joint Order Batching and Picker Routing Problem: Modelled and Solved as a Clustered Vehicle Routing Problem”, Computers & Operations Research, 129, 105168. https://doi.org/10.1016/j.cor.2020.105168
  • Alnahhal, M. ve Noche, B. (2015). “Dynamic Material Flow Control in Mixed Model Assembly Lines”, Computers & Industrial Engineering, 85, 110-119. https://doi.org/10.1016/j.cie.2015.03.009
  • Ardjmand, E., Bajgiran, O.S. ve Youssef, E. (2019). “Using List-Based Simulated Annealing and Genetic Algorithm for Order Batching and Picker Routing in Put Wall Based Picking Systems”, Applied Soft Computing, 75, 106-119. https://doi.org/10.1016/j.asoc.2018.11.019
  • Ardjmand, E., Ghalehkhondabi, I., Young II, W.A., Sadeghi, A., Weckman, G.R. ve Shakeri, H. (2020). “A Hybrid Artificial Neural Network, Genetic Algorithm and Column Generation Heuristic for Minimizing Makespan in Manual Order Picking Operations”, Expert Systems with Applications, 159, 113566. https://doi.org/10.1016/j.eswa.2020.113566
  • Baker, P. ve Canessa, M. (2009). “Warehouse Design: A Structured Approach”, European Journal of Operational Research, 193(2), 425-436. https://doi.org/10.1016/j.ejor.2007.11.045
  • Bottani, E., Montanari, R., Rinaldi, M. ve Vignali, G. (2015). “Intelligent Algorithms for Warehouse Management”, Intelligent Techniques in Engineering Management, Intelligent Systems Reference Library, 87, (Editör: C. Kahraman, S. Çevik Onar), Springer, Cham, 645-667. https://doi.org/10.1007/978-3-319-17906-3_25
  • Calzavara, M., Sgarbossa, F. ve Persona, A. (2019). “Vertical Lift Modules for Small Items Order Picking: An Economic Evaluation”, International Journal of Production Economics, 210, 199-210. https://doi.org/10.1016/j.ijpe.2019.01.012
  • Cano, J.A., Correa-Espinal, A.A., Gómez-Montoya, R.A. ve Cortes, P. (2019). “Genetic Algorithms for the Picker Routing Problem in Multi-Block Warehouses”, International Conference on Business Information Systems, 313-322. https://doi.org/10.1007/978-3-030-20485-3_24
  • Cano, J.A., Cortes, P., Munuzuri, J. ve Correa-Espinal, A. (2024). “Solving the Picker Routing Problem in Multi-Block High-Level Storage Systems Using Metaheuristics”, Flexible Services and Manufacturing Journal, 35(2), 376-415. https://doi.org/10.1007/s10696-022-09445-y
  • Caron, F., Marchet, G. ve Perego, A. (1998). “Routing Policies and COI-Based Storage Policies in Picker-to-Part Systems”, International Journal of Production Research, 36(3), 713-732. https://doi.org/10.1080/002075498193651
  • Caron, F., Marchet, G. ve Perego, A. (2000). “Optimal Layout in Low-Level Picker-to-Part Systems”, International Journal of Production Research, 38(1), 101-117. https://doi.org/10.1080/002075400189608
  • Cergibozan, Ç. ve Tasan, A.S. (2022). “Genetic Algorithm Based Approaches to Solve the Order Batching Problem and A Case Study In A Distribution Center”, Journal of Intelligent Manufacturing, 33(1), 137-149. https://doi.org/10.1007/s10845-020-01653-3
  • Cheng, C.Y., Chen, Y.Y., Chen, T.L. ve Yoo, J.J.W. (2015). “Using A Hybrid Approach Based on the Particle Swarm Optimization and Ant Colony Optimization to Solve A Joint Order Batching and Picker Routing Problem”, International Journal of Production Economics, 170, 805-814. https://doi.org/10.1016/j.ijpe.2015.03.021
  • Çelik, M. ve Süral, H. (2019). “Order Picking in Parallel-Aisle Warehouses with Multiple Blocks: Complexity and A Graph Theory-Based Heuristic”, International Journal of Production Research, 57(3), 888-906. https://doi.org/10.1080/00207543.2018.1489154
  • De Santis, R., Montanari, R., Vignali, G. ve Bottani, E. (2018). “An Adapted Ant Colony Optimization Algorithm for the Minimization of the Travel Distance of Pickers in Manual Warehouses”, European Journal of Operational Research, 267(1), 120-137. https://doi.org/10.1016/j.ejor.2017.11.017
  • de Souza, M.C., de Carvalho, C.R. ve Brizon, W.B. (2008). “Packing Items to Feed Assembly Lines”, European Journal of Operational Research, 184(2), 480-489. https://doi.org/10.1016/j.ejor.2006.09.091
  • DHaen, R., Ramaekers, K., Moons, S. ve Braekers, K. (2024). “A Real‐Life Study on the Value of Integrated Optimization in Order Picking Operations under Dynamic Order Arrivals”, Networks, 84(3), 345-362. https://doi.org/10.1002/net.22237
  • Dijkstra, E.W. (1959). “A Note on Two Problems in Connexion with Graphs”, Numerische Mathematik, (1), 269-271. https://doi.org/10.1007/BF01386390
  • Dorigo, M. ve Gambardella, L.M. (1997). “Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem”, IEEE Transactions on Evolutionary Computation, 1(1), 53-66. https://doi.org/10.1109/4235.585892
  • Dorigo, M. ve Stutzle, T. (2004). Ant Colony Optimization, Cambridge, MIT Press, MA. https://doi.org/10.7551/mitpress/1290.001.0001
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Details

Primary Language Turkish
Subjects Manufacturing and Industrial Engineering (Other)
Journal Section Araştırma Makalesi
Authors

Furkan Ulu 0000-0002-6651-4659

Gülveren Tabansız Göç 0000-0003-4204-1364

Fatih Çavdur 0000-0001-8054-5606

Publication Date April 16, 2025
Submission Date August 27, 2024
Acceptance Date February 10, 2025
Published in Issue Year 2025 Volume: 59 Issue: 2

Cite

APA Ulu, F., Tabansız Göç, G., & Çavdur, F. (2025). Floyd-Warshall ve Karınca Kolonisi Optimizasyonu Algoritmaları ile Depo Rota Planlaması. Verimlilik Dergisi, 59(2), 335-352. https://doi.org/10.51551/verimlilik.1539618
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