An evolutionary stochastic discrete time-cost trade-off method

Abstract

This study introduces a newly developed method for optimized time-cost trade-off under uncertainty. It identifies the optimal execution mode for each project activity that results in minimizing the overall project cost and (or) duration while satisfying a specified joint confidence level of both time and cost. The method uses an evolutionary-based algorithm along with a design generator of experiments and blocking techniques. The developed method accounts for managerial flexibility towards the selection of execution modes. This accommodates experience-based judgement of project managers in this process. Hence, the second fold of the developed method is a completely randomized experiment module that depicts the main effect of changing an activity mode on the project total cost and overall duration. The method provides the decision-maker a guideline for making well-informed implementation strategies. The results obtained demonstrate benefits and accuracy of the developed method and its applicability for large-scale projects.