An Improved Metaheuristic Algorithm for On-site Workshop Availability Cost Problem

TL;DR

This paper introduces ERSA, a novel metaheuristic algorithm, to efficiently solve the complex MOSWACP, significantly reducing costs in construction site resource scheduling compared to traditional methods.

Contribution

It develops a new MILP model for MOSWACP and proposes ERSA, a tailored metaheuristic that outperforms existing algorithms on large-scale instances.

Findings

ERSA outperforms CPLEX, SA, GA, and PSO in large instances.

The proposed model achieves significant cost savings in a real case study.

ERSA effectively manages complex spatial and resource constraints.

Abstract

The Multi-mode Resource Availability Cost Problem (MRACP) optimizes resource availability to minimize usage costs and is a recent project scheduling problem variant. The Multi-Mode On-Site Workshop Availability Cost Problem (MOSWACP) extends MRACP by introducing spatial constraints for On-site Workshops (OSWs) at construction sites. MOSWACP aims to determine the optimal availability level, installation, and dismantling times for OSWs while scheduling activities within spatial and resource limitations. A novel Mixed-Integer Linear Programming (MILP) model is developed, and a metaheuristic algorithm, the Electron Radar Search Algorithm (ERSA), is proposed to solve large-scale instances. ERSA, enhanced with problem-specific operators, outperforms CPLEX in large instances and outperforms Simulated Annealing (SA), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). An actual case study demonstrated significant cost savings using the proposed model. The results and conclusions highlight the effectiveness of the ERSA approach in managing complex project scheduling challenges.