Non-permutation flow shop scheduling problems with uncertain parameters

In this paper, we consider a flow shop scheduling problem with stochastic parameters for the objective of minimizing the makespan. In the problem, process time and release time are considered stochastic variables. We present a mixed integer linear programming (MILP) model for this problem which can generate non-permutation schedules. Chance constrained programming (CCP) approach used to handle the stochastic parameters. Tabu search (TS) is implemented to evolve optimal or near optimal solutions. The MILP model can be used to compute optimal solutions for small-sized problems or to test the performance of presented meta-heuristic algorithm

Keywords:

Flow Shop Scheduling , Mixed Integer Linear Programming , Stochastic Parameters , Tabu Search