Multi-objective particle swarm optimization for construction time-cost tradeoff problems

Reduction in construction project duration is generally linked to additional cost due to more expensive resources required. Hence tradeoff between time and cost is crucial to the efficiency of a construction project. The time-cost tradeoff (TCT) issue has been studied through various multi-objective optimization methodologies to determine an optimal set of activity methods with the objectives of minimizing project duration and total cost. A multi-objective particle swarm optimization that adopts a combined scheme for determining the global best of each particle is presented for solving the TCT problem. The candidate TCT solutions in terms of a set of construction methods for activities are represented through the multidimensional particles. The framework of the combined scheme-based multi-objective particle swarm optimization (CSMOPSO) is developed. Computational analyses are conducted to investigate the performance of the CSMOPSO, including comparison with other methods. This study is expected to provide an alternative solving methodology for the TCT problem and help contractors or engineers plan construction methods with optimal time-cost tradeoff.