An uncertain multi-objective programming model for machine scheduling problem

This paper discusses a parallel machine scheduling problem in which the processing times of jobs and the release dates are independent uncertain variables with known uncertainty distributions. An uncertain programming model with multiple objectives is obtained, whose first objective is to minimize the maximum completion time or makespan, and second objective is to minimize the maximum tardiness time. A genetic algorithm is employed to solve the proposed uncertain machine scheduling model, and its efficiency is illustrated by some numerical experiments.