Application of Improved Particle Swarm Optimization in Construction Contractors' Selection and Optimization

With the increasing investment sale and improving technology level of the construction project, it has been a universal phenomenon that several construction enterprises jointly completed a large-sale project. Therefore, the problem of construction contractor's selection has emerged. In this paper, the construction contractor's selection and optimization with the aim of minimizing the construction project cost within the required duration, was described and modeled. Then this paper developed a new algorithm to find the optimal combination of contractors to achieve the minimum cost with in the required duration. And the proposed algorithm modified a population-based search procedure, particle swarm optimization, by adopting an elite archiving scheme to store nondominated solutions and by aptly using members of the archive to direct further search. Moreover, the termination of the proposed algorithm was set to that no new members have entered into the elite archive. In addition, through a practical case, the proposed algorithm is shown effective and efficient in construction contractors' selection and optimization.