A chance-constrained approach to stochastic line balancing problem

In this paper, chance-constrained 0–1 integer programming models for the stochastic traditional and U-type line balancing (ULB) problem are developed. These models are solved for several test problems that are well known in the literature and the computational results are given. In addition, a goal programming approach is presented in order to increase the system reliability, which is arising from the stochastic case.