This paper presents an effective stochastic algorithm that embeds a large neighborhood decomposition technique into variable search for solving the permutation flow-shop scheduling problem. The first constructs as seed using recursive application of extended two-machine In this method, jobs are recursively decomposed two separate groups, and, each group, optimal is calculated based on Then over...

Stochastic, as well fuzzy uncertainty, can be found in most real-world systems. Considering both types of uncertainties simultaneously makes optimization problems incredibly challenging. In this paper, we analyze the permutation flow shop problem (PFSP) with stochastic and processing times. The main goal is to find solution (permutation jobs) that minimizes expected makespan. However, due exist...

This paper addresses minimizing the makespan of the distributed permutation flow shop scheduling problem. In this problem, there are several parallel identical factories or flowshops each with series of similar machines. Each job should be allocated to one of the factories and all of the operations of the jobs should be performed in the allocated factory. This problem has recently gained attent...

In industries machine maintenance is used in order to avoid untimely machine fails as well as to improve production effectiveness. This research regards a permutation flow shop scheduling problem with aging and learning effects considering maintenance process. In this study, it is assumed that each machine may be subject to at most one maintenance activity during the planning horizon. The objec...