BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Rodrigo Sara (University of Moratuwa, Sri Lanka), Kosgoda Dilina (University of Moratuwa, Sri Lanka), Fernando W. Madushan (University of Moratuwa, Sri Lanka), Nielsen Peter (Aalborg University Copenhagen, Denmark), Thibbotuwawa Amila (University of Moratuwa, Sri Lanka)
Optimizing Fresh-cut Flower Distribution Using Vehicle Routing Problem for Perishable Goods
LogForum, 2024, vol. 20, nr 1, s. 23-37, tab., wykr., bibliogr. 19 poz.
Dystrybucja, Przewozy towarowe, Transport samochodowy, Logistyka dystrybucji
Distribution, Cargo transportation, Motor transport, Distribution logistics
Background: Achieving optimization in complex distribution operations necessitates significant attention to the distinctive operating procedures and features of various distribution systems. One particularly challenging distribution operation is the transportation of fresh-cut flowers. This process demands that a required quality be maintained at every stage, spanning from the flower growers, wholesalers, and retailers to the end customer. Failure to uphold the required level of freshness can lead to adverse outcomes such as decreased profits, customer attrition, and a tarnished reputation. To investigate this complex distribution process, fresh flower distribution was studied using data from a reputed floral company in Sri Lanka with the aim of finding the optimal set of routes for the distribution of fresh-cut flowers. Methods: Vehicle Routing Problem (VRP) variants were employed and the 'Capacitated Vehicle Routing Problem with Time Windows for Perishable Goods with Single Depot' (CVRPTWfPGSD) was introduced. A hybrid method combining both heuristics and metaheuristics was selected as the methodology by considering several factors such as complexity, solution type, and execution time. The initial solution construction phase adopted the Path Cheapest Arc (PCA) heuristic. To further improve solution quality, the Guided Local Search (GLS) metaheuristic was applied. Results: This CVRPTWfPGSD model is validated for real-world scenarios, as it does not violate the maximum allowable perishability time provided for each vehicle. Three experiments were conducted by varying the vehicle fleet to measure the applicability of the model under different circumstances to decide on a better vehicle combination while minimizing total distribution time. Based on this analysis, it can be concluded that the composition of the vehicle fleet has a substantial influence on freshness levels and distribution times. Conclusions: Optimizing the distribution of fresh-cut flowers using VRP assists in reducing spoilage and waste by ensuring that flowers are transported under the best possible conditions. The application of this model holds immense value for floral companies as it offers assistance when planning their distribution network. Specifically, it can assist in identifying optimal routes that maximize freshness with minimum distribution time and an optimal set of vehicles.(original abstract)
Full text
  1. Ahumada, O., & Villalobos, J. R. (2011). A tactical model for planning the production and distribution of fresh produce. Annals of Operations Research, 190(1), 339-358.
  2. Calvete, H. I., Galé, C., Oliveros, M. J., & Sánchez-Valverde, B. (2004). Vehicle routing problems with soft time windows: an optimization based approach. Monografías Del Seminario Matemático García de Galdeano, 31(January 2014), 295-304.
  3. Esmaili, M. H., & Mousavi, S. M. (2020). An integrated perishable inventory routing problem with consistent driver services and fresh product delivery using possibility and necessity measures. International Journal of Industrial Engineering and Production Research, 31(2), 231-242.
  4. Fernando, M., D. D. DHANANJAYA, J.A MUNASINGHE, Amal S. KUMARAGE, T. SIVAKUMAR, & A.S. PERERA. (2021). Post-Processing of GPS Data for Bus Link Speed Determination based on GIS. Journal of the Eastern Asia Society for Transportation Studies, 14(January 2022), 1179-1192.
  5. Fernando, M., Thibbotuwawa, A., Perera, H. N., & Chandima Ratnayake, R. M. (2022). Applying a Capacitated Heterogeneous Fleet Vehicle Routing Problem with Multiple Depots Model to Optimize a Retail Chain Distribution Network. IEEE International Conference on Industrial Engineering and Engineering Management, 2022-Decem, 588-592.
  6. Fernando, M., Thibbotuwawa, A., Perera, H. N., & Ratnayake, R. M. C. (2022). Close-Open Mixed Vehicle Routing Optimization Model with Multiple Collecting Centers to Collect Farmers' Perishable Produce. 2022 International Conference for Advancement in Technology, ICONAT 2022, 1-8.
  7. FloraLife. (2023). Care and Handling Best Practices (p. 0). LivRio Magazine.
  8. Galarcio Noguera, J. D., Hernández Riaño, H. E., & López Pereira, J. M. (2018). Hybrid PSO-TS-CHR Algorithm Applied to the Vehicle Routing Problem for Multiple Perishable Products Delivery. Communications in Computer and Information Science, 916, 61-72.
  9. Gupta, J., & Dubey, R. K. (2018). Factors Affecting Post-Harvest Life of Flower Crops. International Journal of Current Microbiology and Applied Sciences, 7(1), 548-557.
  10. Halevy, A. H., & Mayak, S. (2011). Senescence and Postharvest Physiology of Cut Flowers-Part 2. Horticultural Reviews, 59-143.
  11. Malindretos, G. (2018). Cut-flowers supply chain. September 2016.
  12. Perron, L., & Furnon, V. (2023). OR-Tools.
  13. Ruiz-Garcia, L., & Lunadei, L. (2010). Monitoring Cold Chain Logistics by Means of RFID. In C. Turcu (Ed.), Sustainable Radio Frequency Identification Solutions. IntechOpen.
  14. Shaabani, H. (2022). A literature review of the perishable inventory routing problem. Asian Journal of Shipping and Logistics, 38(3), 143-161.
  15. Sirisaranlak, P. (2017). The Cool Supply Chain Management for Cut Flowers oncordance for Self- English Writing of. 2004.
  16. Taillard, Eric; Badeau, P; Gendreau, M. (1997). A tabu search heuristic for the VRP with soft TW. In Transportation Science (Vol. 31, Issue 2, pp. 170-186).
  17. Toth, P., & Vigo, D. (2001). THE VEHICLE ROUTING PROBLEM. Society for Industrial and Applied Mathematics Philadelphia.
  18. Van Rijswick, C. (2015). World Floriculture Map 2015. Rabobank Industry Note, # 475(January), 1-4.
  19. Wang, X. P., Wang, M., Ruan, J. H., & Li, Y. (2018). Multi-objective optimization for delivering perishable products with mixed time windows. In Advances in Production Engineering And Management (Vol. 13, Issue 3, pp. 321-332).
Cited by
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu