A bi-objective genetic algorithm approach to risk mitigation in project scheduling

Abstract

A problem of risk mitigation in project scheduling is formulated as a bi-objective optimization problem, where the expected makespan and the expected total cost are both to be minimized. The expected total cost is the sum of four cost components: overhead cost, activity execution cost, cost of reducing risks and penalty cost for tardiness. Risks for activities are predefined. For each risk at an activity, various levels are defined, which correspond to the results of different preventive measures. An MIP model and a heuristic solution approach based on genetic algorithms (GAs) is proposed. GAs provide a fast and effective solution approach to the problem.