Integrated genetic algorithm and its applications for construction resource optimization

Construction project resource scheduling problems have been interesting and challenging subjects of extensive research for several decades in the optimization study area in order to put them in practical application. Recently, the integrated genetic algorithm rather than the stand-alone GA is being increasingly applied to solve the problems. An adaptive hybrid genetic algorithm search simulator (AHGASS) for resource scheduling problems has been developed in the previous stage of this research. Previous work outlined the strategies and practical procedures for the algorithm development, but did not deal with algorithm performance with regard to algorithm runtime, especially against runtime used in generating optimality. Since the major drawback of using GA is a great length of time required, it is meaningful to investigate the significance in algorithm runtime between AHGASS and optimality. To address this issue, this paper attempts to investigate the difference in algorithm performance with regard to algorithm runtime.