Document Type : Research Paper


1 Department of Industrial and Production Engineering, National Institute of Textile Engineering and Research, Savar, Bangladesh.

2 Department of Industrial and Production Engineering, Shahjalal University of Science and Technology, Sylhet, Bangladesh.

3 Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh.


Bangladesh is blessed with various agro-based natural resources like Date sap, extracted from date trees. As this date sap is found in rural areas in large quantities annually but a very small fraction is converted into some value-added delicious foods at a domestic level while a large portion is left underutilized due to negligence, improper collection, and preservation system from the industry level. The processed delicious foods have conspicuous demand in the national market due to their nutritious value and the growth of the national economy. Despite its economic importance, very little researches have been conducted in this field for its industrial processing. So, this research implies to improve this straggled sector providing much attention for collecting raw sap from source and processing into value-added products from industrial level cost-effectively. The key objectives of this paper are to determine optimal facility location for processing date sap and set vehicle routes that can pick up date sap from source to processing plant simultaneously curtailing operational transportation costs. Initially, a Mixed Integer Linear Programming (MILP) model is introduced to determine optimal facility location. Besides, the Large Neighborhood Search (LNS) algorithm has been used to find the optimal set of vehicle routes. This paper outlines a summary of final results that Jessore (A south-western city in Bangladesh) is an optimal plant location and 10 vehicles are necessary for covering 15 areas which ultimately optimize the total supply time, respecting constraints concerning routing, timing, capacity, and supply as well transportation costs.


Main Subjects

  1. Tirkolaee, E., Abbasian, P., Soltani, M., & Ghaffarian, S. A. (2019). Developing an applied algorithm for multi-trip vehicle routing problem with time windows in urban waste collection: a case study. Waste management & research37(1_suppl), 4-13.
  2. Tirkolaee, E. B., Goli, A., Bakhshi, M., & Sangaiah, A. K. (2019). An Efficient biography-based optimization algorithm to solve the location routing problem with intermediate depots for multiple perishable products. In deep learning and parallel computing environment for bioengineering systems(pp. 189-205). Academic Press.
  3. Singamsetty, P., & Thenepalle, J. (2021). Designing optimal route for the distribution chain of a rural LPG delivery system. International journal of industrial engineering computations12(2), 221-234.
  4. Sangaiah, A. K., Tirkolaee, E. B., Goli, A., & Dehnavi-Arani, S. (2020). Robust optimization and mixed-integer linear programming model for LNG supply chain planning problem. Soft computing24(11), 7885-7905.
  5. Goli, A., Aazami, A., & Jabbarzadeh, A. (2018). Accelerated cuckoo optimization algorithm for capacitated vehicle routing problem in competitive conditions. International journal of artificial intelligence16(1), 88-112.
  6. Tirkolaee, E. B., Alinaghian, M., Hosseinabadi, A. A. R., Sasi, M. B., & Sangaiah, A. K. (2019). An improved ant colony optimization for the multi-trip Capacitated Arc Routing Problem. Computers & electrical engineering77, 457-470.
  7. Goli, A., & Malmir, B. (2020). A covering tour approach for disaster relief locating and routing with fuzzy demand. International journal of intelligent transportation systems research18(1), 140-152.
  8. Tirkolaee, E. B., Goli, A., & Weber, G. W. (2020). Fuzzy mathematical programming and self-adaptive artificial fish swarm algorithm for just-in-time energy-aware flow shop scheduling problem with outsourcing option. IEEE transactions on fuzzy systems28(11), 2772-2783.
  9. Tirkolaee, E. B., Goli, A., Weber, G. W., & Szwedzka, K. (2020). A novel formulation for the sustainable periodic waste collection arc-routing problem: a hybrid multi-objective optimization algorithm. In logistics operations and management for recycling and reuse(pp. 77-98). Springer, Berlin, Heidelberg.
  10. Tirkolaee, E. B, Hadian, S., & Golpira, H. (2019). A novel multi-objective model for two-echelon green routing problem of perishable products with intermediate depots. Journal of industrial engineering and management studies6(2), 196-213.
  11. Tirkolaee, E. B., Hosseinabadi, A. A. R., Soltani, M., Sangaiah, A. K., & Wang, J. (2018). A hybrid genetic algorithm for multi-trip green capacitated arc routing problem in the scope of urban services. Sustainability10(5), 1366.
  12. Tirkolaee, E. B., Mahdavi, I., & Esfahani, M. M. S. (2018). A robust periodic capacitated arc routing problem for urban waste collection considering drivers and crew’s working time. Waste management76, 138-146.
  13. Yantong, L. I., Feng, C. H. U., Zhen, Y. A. N. G., & Calvo, R. W. (2016). A production inventory routing planning for perishable food with quality consideration. Ifac-papersonline49(3), 407-412.
  14. Erdoğan, G. (2015). User’s manual for VRP spreadsheet solver. Retrieved from
  15. Erdoğan, G. (2017). An open source spreadsheet solver for vehicle routing problems. Computers & operations research84, 62-72.
  16. Hong, L. (2012). An improved LNS algorithm for real-time vehicle routing problem with time windows. Computers & operations research39(2), 151-163.
  17. Musavi, M., & Bozorgi-Amiri, A. (2017). A multi-objective sustainable hub location-scheduling problem for perishable food supply chain. Computers & industrial engineering113, 766-778.
  18. Expósito, A., Raidl, G. R., Brito, J., & Moreno-Pérez, J. A. (2017, February). GRASP-VNS for a periodic VRP with time windows to deal with milk collection. International conference on computer aided systems theory(pp. 299-306). Springer, Cham.
  19. Mei, H., Jingshuai, Y., Teng, M. A., Xiuli, L. I., & Ting, W. (2017). The modeling of milk-run vehicle routing problem based on improved CW algorithm that joined time window. Transportation research procedia25, 716-728.
  20. Kim, J., Realff, M. J., Lee, J. H., Whittaker, C., & Furtner, L. (2011). Design of biomass processing network for biofuel production using an MILP model. Biomass and bioenergy35(2), 853-871.
  21. Pauls-Worm, K. G., Hendrix, E. M., Haijema, R., & van der Vorst, J. G. (2014). An MILP approximation for ordering perishable products with non-stationary demand and service level constraints. International journal of production economics157, 133-146.
  22. Tirkolaee, E. B., Goli, A., Faridnia, A., Soltani, M., & Weber, G. W. (2020). Multi-objective optimization for the reliable pollution-routing problem with cross-dock selection using Pareto-based algorithms. Journal of cleaner production276, 122927.
  23. Desrochers, M., & Laporte, G. (1991). Improvements and extensions to the Miller-Tucker-Zemlin subtour elimination constraints. Operations research letters10(1), 27-36.