Time-cost-quality trade-off model for subcontractor selection using discrete particle swarm optimization algorithm

In general, construction projects consist of several work packages. The general contractors usually tend to sublet these work packages to various subcontractors. In such cases, general contractors are responsible for the quality of the work packages performed by the selected subcontractors. In this context, the success of a construction project and thereby the general contractor depends on the performances of the subcontractors. Therefore, one of the main problems that a general contractor faces is the selection of the right subcontractors for the right work packages. In most cases, general contractors make this decision at the beginning of the project and they have to evaluate potential subcontractors' performances in terms of time, cost and quality during the subcontractor selection process. After this evaluation process, they select an optimal combination of subcontractors that will carry out the work packages in the project. It is not an easy task for a general contractor to select the most appropriate combination, which balances the trade-off between time, cost and quality. The main objective of this study is to generate a discrete particle swarm optimization algorithm (DPSO), which will assist general contractors to select the most appropriate subcontractors that will carry out different work packages in a construction project considering the trade-off between time, cost and quality. In order to illustrate how this algorithm can be used in the subcontractor selection problem, the data obtained from a trade centre project is used. Findings of the research revealed that the proposed algorithm is satisfactory.