Applying self-adaptive ant colony optimization for construction time-cost optimization

Abstract

The time-cost optimization (TCO) problem is a multiobjective problem, which attempts to strike a balance between resource allocation costs and project schedule duration. In this paper, a self-adaptive ant colony optimization (SACO) with changing parameters based on information entropy has been employed to model time-cost optimization problem, which overcome the intrinsic weakness of premature of the basic ant colony optimization (ACO) by adjusting parameters according to mean information entropy of the ant system. A computer simulation with Matlab7.0 based on a prototype example has been carried out on the basis of SACO for TCO problem. The test results show that the SACO for TCO model can generate a more optimal cost under the same duration and achieve a better Pareto front than other models. Therefore, the SACO can be regarded as a useful approach for solving construction project TCO problems.