Although the deterministic flow shop model is one of the most widely studied problems in scheduling theory, its stochastic analog has remained challenging. No computationally efficient optimization procedure exists even for the general two-machine version. In this paper, we describe three heuristic procedures for the stochastic two-machine flow shop problem and report on computational experimen...

Although the deterministic flow shop model is one of the most widely studied problems in scheduling theory, its stochastic analog has remained a challenge. No computationally efficient optimization procedure exists even for the general two-machine version. In this paper, we describe three heuristic procedures for the stochastic two-machine flow shop problem and report on computational experimen...

Scheduling is an important process widely used in manufacturing, production, management, computer science, and so on. Appropriate scheduling can reduce material handling costs and time. Finding good schedules for given sets of jobs can thus help factory supervisors effectively control job flows and provide solutions for job sequencing. In simple flow shop problems, each machine operation center...

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A scheduling system is proposed and developed for a special type of flow shop. In this flow shop there is one machine at each stage. A job may require multiple operations at each stage. The first operation of a job on stage j cannot start until the last operation of the job on stage j-1 has finished. Preemption of the operations of a job is not allowed. The flow shop that we consider has anothe...

The problem of minimizing the expected number of tardy jobs in a dynamic m machine flow shop i.e., Fm�rj�E�∑Uj� is studied in this research. It is assumed that the jobs with deterministic processing times and stochastic due dates arrive dynamically and randomly to the flow shop cell. The due date of each job is assumed to be normally distributed with known mean and variance. A dynamic method is...

We consider a stochastic online scheduling environment, where jobs with stochastic processing requirements arrive over time and the objective is to minimize the total weighted completion time. We show that any nondelay algorithm is asymptotically optimal for the stochastic online single machine, flow shop and uniform parallel machine problems under some mild assumptions.