An Application of Genetic Algorithms to Time-Cost-Quality Trade-off in Construction Industry

Abstract

Time, cost and quality are used for measuring project success. So, they are considered the most important objectives in construction projects. Project managers should deliver their project on time with minimum cost and at a certain quality level. To get these conflicting objectives, project managers introduce many possible methods of execution (modes) for each activity in the project. This paper presents an optimization model that supports project managers and decision makers in performing this challenging task and leads to identification of the best solution. Developed model is based on Genetic Algorithms which have many advantages over traditional optimization techniques and considered suitable for more than one objective function. The developed Genetic Algorithms model considers target function, design variables affecting that target, and problem constraints. Through application to two projects, the model feasibility is examined. The results show that the proposed approach can help the practitioners in considering different modes for activities and easily find minimum cost for a certain project time meeting the quality requirements. The model can easily reach the best solution from huge number of solutions in reasonable running time. In addition, the results tell that the present method can be used in generating a group of optimal solutions.

Key words: construction projects; time-cost-quality; trade-off; optimization; Genetic Algorithms