Minimizing the number of tardy jobs in stochastic setting using chance constrained programming

In this research, two different scheduling problems i.e., single machine scheduling problem ( liiiUi) and two machine flow shop scheduling problem with a common due date (F2 1di =dl I U;) are investigated in stochastic setting. The objective is minimizing the number of tardy jobs in nonpreemptive static listpolicy. It is assumed that the processing times of jobs are independent random variables. The stochastic problems aresolved based on chance constrained programming approach. Anequivalent deterministic problem is generated for each stochastic problem by linearization of the chance constraints. Then, thegenerated deterministic problems are solved using efficient algorithms, which have been developed for the deterministicversion of the problems. A numerical example is presented to illustrate the solution method

Keywords:

component , Stochastic scheduling , single machine scheduling , flow shop scheduling , tardy jobs , chance constrained programming