Utilizing arithmetic optimization algorithm for optimizing time and cost in construction project

The time-cost trade-off problem (TCTP) presents a significant challenge in construction management, requiring a balance between project duration and associated costs for successful completion.This study evaluates the performance of an arithmetic optimization algorithm (AOA) for solving the TCTP.AOA integrates non-dominated sorting (NDS) to generate Pareto-optimal solutions that address both time and cost objectives.The methodology involves testing the AOA on three case studies representing small-and medium-scale construction projects with 18, 29, and 63 activities.Comparative analyses with traditional metaheuristic algorithms, such as ant colony optimization, genetic algorithms, and particle optimization algorithms, reveal that NDS-AOA delivers competitive results, particularly in smaller projects, that achieve lower costs and faster computation times.However, its effectiveness decreases in medium-scale projects, indicating scalability limitations.Numerical tests suggest that while AOA is wellsuited for small to medium projects, it requires further enhancements, such as hybridization with other techniques, to effectively handle larger-scale problems.