Genetic Algorithm-Based Chaos Clustering Approach for Optimizing Construction Time-Cost Tradeoff Problems

Abstract

Time-cost tradeoff (TCT) problems have been studied extensively in construction management literatures. TCT decisions, as combinatorial optimization problems, are difficult to find out their optimal solutions. However, Genetic Algorithms (GA) coupled with chaos and K-means clustering approach, named KCGA, can tackle these problems effectively. KCGA has successfully incorporated two opposite properties contraction and diversity which come from Kmeans and chaos, respectively. K-means is to speed up the contraction and chaos to diversify population in GA. The hybrid KCGA approach was verified by empirical construction management example with excellent performance in terms of computation efficiency and estimation accuracy while comparing with other algorithms separately.