A Novel Robust Model for Discrete Time-Cost Trade off Problem

In project scheduling, the activity durations can often be reduced by dedicating additional resources. Time/Cost Trade-off Problem considers the compromise between the total cost and project duration. The discrete version of the problem assumes a number of time/cost pairs, so called modes, and selects a mode for each activity. In this paper, we consider the Discrete Time/Cost Trade-off Problem. We study the problem of minimizing total cost subject to a deadline on project duration so called Deadline problem. Projects are often subject to various sources of uncertainties that have a negative impact on activity durations and costs. Therefore, it is crucial to develop effective approaches to generate robust project schedules that are less vulnerable to disruptions caused by non-controllable factors. We propose a novel robust model for the DTCTP in which interval uncertainty is assumed for the unknown cost parameters. We use genetic algorithms to solve the proposed robust optimization model. Our computational results on large-sized problem instances have revealed the satisfactory behavior of our algorithms.