Robust and Stable Flow Shop Scheduling Problem under Uncertain Processing Times and Machines’ Disruption

Abstract

This paper presents a predictive robust and stable approach for a two-machine flow shop scheduling problem with machine disruption and uncertain job processing time. Indeed, a general approach is proposed that can be used for robustness and stability optimization in an m-machine flow shop or job shop scheduling problem. The robustness measure is the total expected realized completion time. The expected sum of squared aberration between each jobs' completion time in the realized and initial schedules is the stability measure. We proposed and compared two methods to deal with such an NPhard problem; a method based on decomposing the problem into subproblem and solving each subproblem, and a theorem-based method. The extensive computational results indicated that the second method has a better performance in terms of robustness and stability, especially in large-sized problems. In other words, the second method is preferable because of the better manufacturer responsiveness to the customer and the production staff satisfaction enhancement.The expected real completion time of job j on the machine i

Distributed Production Assembly Scheduling with Hybrid Flowshop in Assembly Stage

“…As previously proven in the introduction section, the distributed production-assembly scheduling problem with hybrid flowshop in assembly stage is NP-Hard and solving large sizes is not possible using the model. Abtahi and Sahraeian [28] presented two-machine flow shop scheduling problem that is NP-Hard, too. Different methods are proposed to solve the distributed scheduling problem.…”

A joint optimization model for production scheduling and preventive maintenance interval

“…They used Gams software to solve their model. Abtahi and Sahraeian [22] presented a predictive robust and stable approach for a two-machine flow shop scheduling problem with machine disruption and uncertain job processing time. A general approach is proposed that can be used for robustness and stability optimization in an m-machine flow shop or job shop scheduling problem.…”