An improved metaheuristic algorithm for on-site workshop availability cost problem
نویسندگان
1 Department of Industrial and System Engineering, University of Minnesota, Minneapolis, MN, 55455, USA.
2 Concordia University, Concordia Institute for Information and Systems Engineering, Montreal, QC, 1455, Canada.
doi
10.22105/jarie.2025.488174.1707چکیده
The Multi-Mode On-Site Workshop Availability Cost Problem (MOSWACP) extends the Multi-Mode Resource Availability Cost Problem (MRACP), addressing resource availability optimization under spatial and resource constraints at construction sites. The problem focuses on determining the optimal availability levels, installation, and dismantling schedules for On-Site Workshops (OSWs) while adhering to spatial limitations and project deadlines. This study introduces a novel Mixed-Integer Linear Programming (MILP) model to represent MOSWACP, ensuring efficient resource allocation and activity scheduling. We propose the Electron Radar Search Algorithm (ERSA), a problem-specific metaheuristic enhanced with tailored improvement operators to solve large-scale instances. ERSA demonstrates superior performance compared to Simulated Annealing (SA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), as well as the exact solver CPLEX, particularly for large-scale problems. Applying to a real-world trailer production project yielded significant cost savings, reducing resource costs by 33.99% ($11750) compared to traditional methods. The findings highlight the effectiveness of the proposed methodology in managing complex Project Scheduling Problems (PSPs), offering practical implications for cost-efficient resource management in construction projects.
