Abstract
Construction projects are generally subject to uncertainty, which influences the realization of time-cost tradeoff in project management. This paper addresses a time-cost tradeoff problem under uncertainty, in which activities in projects can be executed in different construction modes corresponding to specified time and cost with interval uncertainty. Based on multiobjective robust optimization method, a robust optimization model for time-cost tradeoff problem is developed. In order to illustrate the robust model, nondominated sorting genetic algorithm-II (NSGA-II) is modified to solve the project example. The results show that, by means of adjusting the time and cost robust coefficients, the robust Pareto sets for time-cost tradeoff can be obtained according to different acceptable risk level, from which the decision maker could choose the preferred construction alternative.
Highlights
Widespread uncertainty in projects will directly affect the achievement of the project schedule and cost management goals
When x = x0, the value range of functional vector can be shown as objective sensitivity region (OSR) in f, and solid black spot is nominal value f(x0, p0)
worstcase objective sensitivity region (WCOSR) of f(x0, p) is through f(x0, p) sensitive area of the target objective function corresponding to the maximum point and the straight line parallel to the axis of the enclosed area
Summary
Widespread uncertainty in projects will directly affect the achievement of the project schedule and cost management goals. Shou and Wang [8] studied project scheduling problem when activity period was a discrete random variable They proposed robust optimization model and designed the genetic algorithms for the model. Wang [9] researched project scheduling problem when time and cost are discrete random variables He proposed DSPSP model in pursuit of the biggest expected value of net present value and solved two instances to confirm the superiority of the model by simulated annealing algorithm. The research established and compared three different robust optimization models of time-cost tradeoff problems and explored exact and heuristic algorithms for those models. This paper researched the DTCTP problem with uncertainties of both time and cost and used multiobjective robust optimization to build robust model of time and cost and at last employed NSGA-II to analyze engineering example
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