MATLAB-Based Linear Programming Techniques for Resource Optimization in Construction Management: A Review

Abstract

The construction industry operates in highly resource-constrained environments where effective allocation of materials, labor, equipment, and financial resources directly influences project cost, duration, and productivity. Despite the widespread use of Linear Programming (LP) and Mixed-Integer Linear Programming (MILP) approaches in construction planning, limited review studies explicitly examine how these optimization models are integrated within MATLAB-based computational environments. With an emphasis on MATLAB-supported LP/MILP applications for resource optimization in construction management, this study provides an organized assessment of 25 research articles published between 2018 and 2025. Applications are divided into four categories by the review: integrated cost-time optimization frameworks, manpower allocation, material planning, and equipment scheduling. The use of solvers (especially MATLAB's linprog solver and Optimization Toolbox), methodological trends, and new developments toward multi-objective and digitally integrated optimization models are all critically examined. The results show that hybrid and resilience-oriented optimization frameworks are increasingly replacing deterministic single-objective models. Despite demonstrated computational efficiency and modeling flexibility, challenges remain in real-time implementation under dynamic site conditions. The study contributes by synthesizing recent advancements and identifying research gaps related to uncertainty modeling and digital construction integration, thereby providing guidance for future MATLAB-based optimization research in construction management.