Modified Adaptive Weighting Method for time-Cost Trade-off Problem based on Ant Colony Optimization

The trade-off between the project duration and total cost is one of the most important facets of construction project planning. For time-cost trade-off problem, as combinatorial optimization problems one can apply heuristics or mathematical programming. The primary disadvantage of mathematical programming models is that they cannot solve large and complex networks effectively. This paper incorporates a new evolutionary algorithm —ant colony optimization (ACO) algorithm to deal with the TCTP. In this paper An applicable ACO algorithm for time-cost optimization with a systematic developed computer program is implemented successfully. In addition, an 18 activity time-cost problem is used to evaluate the performance of the proposed algorithm. The results indicate that the ACO algorithm has the ability to search through a global optimal space without being stuck in a local optimal solution, and by incorporating with the adaptive weight approach (AWA), the ACO algorithm not only find out the optimal solution, but also define the Pareto front as well. Hence the proposed approach in this paper is much adaptive and suitable for tackling TCTP, which is useful and beneficial for decision-making on the trade-off between project duration and total cost.

Keywords:

Time-Cost Trade-off , Multi-objective Optimization , Pareto Front , ACO