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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67770
Volume:
10 |
10 |
Oct 2026
Pages:
1-16
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Operations Research
Anil Surendra Modi School of Commerce
Operations Research
Anil Surendra Modi School of Commerce
Operations Research
Anil Surendra Modi School of Commerce
Operations Research
Anil Surendra Modi School of Commerce
Operations Research
Anil Surendra Modi School of Commerce
Operations Research (OR) is a scientific discipline that uses mathematical modelling, statistical analysis, and algorithmic optimisation to support complex decision-making under resource limitations and operational constraints (Taha, 2017). An OR study systematically converts an unstructured real-world operational challenge into a structured mathematical abstraction consisting of decision variables, an objective function, and a set of explicit physical or functional constraints. Once formalised, the model is solved using exact analytical procedures, mathematical programming, or approximate heuristics, followed by rigorous validation against historical or real-time operational data. In industrial logistics and material handling, Warehouse Space Allocation is a core domain where OR methodologies significantly outperform manual rules of thumb or empirical intuition. Modern warehouses operate as high-velocity distribution nodes where millions of physical Stock Keeping Units (SKUs) must be received, stored, picked, and dispatched within strict time windows. Facility managers face continuous multi-factorial trade-offs: maximising cubic storage space utilisation while simultaneously minimising order picking travel distance, preventing congestion in pick aisles, balancing rack structural load limits, and maintaining operational flexibility. Mathematical modelling converts these conflicting requirements into solvable optimisation problems, providing quantifiable improvements in warehouse throughput, labour efficiency, and floor space productivity.
KEYWORDS
Managing warehouse space allocation efficiently is critical to modern supply chain operations. The evolution of Operations Research in this domain, moving from basic linear programming and index rules (such as COI) to complex mixed-integer programming, machine learning highlights the growing complexity and velocity of modern distribution centres. The five benchmark studies analysed demonstrate that optimising warehouse space is not merely a task of packing items into available rack volume; it requires balancing picking travel distances, slot dimensions, product affinity, dynamic demand, and structural safety limits. As e-commerce growth demands faster order fulfilment and higher space efficiency, integrating advanced OR methodologies into automated Warehouse Management Systems will remain a primary driver of supply chain efficiency, cost reduction, and operational resilience.
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Publication Date
10/10/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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