IMPROVING WAREHOUSE SPACE ALLOCATION WITH LINEAR PROGRAMMING: AN ILLUSTRATIVE OPERATIONS RESEARCH STUDY
A distribution warehouse must decide how much of every product it will keep in every storage zone each week. These decisions determine the use of space, the handling workload and whether demand is met. This study shows how linear programming (LP), a core technique of Operations Research (OR), can help with that decision. We formulate a warehouse space allocation model for an illustrative regional distributor with four product families and three storage zones. We maximize net weekly contribution subject to zone capacity, demand limits, minimum service levels and product–zone compatibility; we solve it as an integer linear programme and the optimal plan is compared with a rule-of-thumb plan. The optimal plan earns 1,095,300 currency units (CU) per week compared to 1,094,100 CU for the rule, a difference of 0.11%. The more informative result is the sensitivity analysis: each additional racking position is worth about 1,500 CU per week up to 400 and about 1,220 CU per week after that. The data are illustrative, and so this study demonstrates a method and does not provide evidence about any real warehouse.
Khanjio, S., Desai, S., Goyal, S., Jagwayan, S. & Sabharwal, S. (2026). Improving Warehouse Space Allocation with Linear Programming: An Illustrative Operations Research Study. International Journal of Science, Strategic Management and Technology, 02(10), 1-9. https://doi.org/10.55041/ijsmt.v2i10.041
Khanjio, Shraddha, et al.. "Improving Warehouse Space Allocation with Linear Programming: An Illustrative Operations Research Study." International Journal of Science, Strategic Management and Technology, vol. 02, no. 10, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i10.041.
Khanjio, Shraddha,Shreet Desai,Siddhant Goyal,Shriya Jagwayan, and Shaurya Sabharwal. "Improving Warehouse Space Allocation with Linear Programming: An Illustrative Operations Research Study." International Journal of Science, Strategic Management and Technology 02, no. 10 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i10.041.
Dantzig, G. B. (1963). Linear programming and extensions. Princeton University Press.
Eiselt, H. A., & Sandblom, C.-L. (2007). Linear programming and its applications. Springer.
Frazelle, E. (2002). World-class warehousing and material handling. McGraw-Hill.
Fylstra, D., Lasdon, L., Watson, J., & Waren, A. (1998). Design and use of the Microsoft Excel Solver. Interfaces, 28(5), 29–55. https://doi.org/10.1287/inte.28.5.29
Gu, J., Goetschalckx, M., & McGinnis, L. F. (2007). Research on warehouse operation: A comprehensive review. European Journal of Operational Research, 177(1), 1–21.
Hillier, F. S., & Lieberman, G. J. (2015). Introduction to operations research (10th ed.). McGraw-Hill.
Rouwenhorst, B., Reuter, B., Stockrahm, V., van Houtum, G. J., Mantel, R. J., & Zijm, W. H. M. (2000). Warehouse design and control: Framework and literature review. European Journal of Operational Research, 122(3), 515–533.
Taha, H. A. (2017). Operations research: An introduction (10th ed.). Pearson.