Scheduling problem solving using genetic and greedy algorithms. (2017)

• Record Type: Journal Article
• Authors: Muthiah, A.; Rajkumar, R.
• Is Part Of: International journal of computer aided engineering and technology. Volume 9:Number 2(2017)
• Page Start: 207
• Page End: 217
• Publication Date: 2017
• Subjects: job shop scheduling -- genetic algorithms -- greedy algorithms -- sequence dependant setup times; Computer-aided engineering -- Periodicals; 620.00285
• Languages: English
• ISSNs: 1757-2657

Abstract

Scheduling is an important tool for manufacturing and engineering, where it can have a major impact on the productivity of a process. In manufacturing, the purpose of scheduling is to minimise the production time and costs. Production scheduling aims to maximise the efficiency of the operation and reduce costs. The following approaches are used to solve the job shop problem. We keep all of our machines well-maintained to prevent any problems, but there is no way to completely prevent down-time. We can work to get our batch sizes as small as is reasonably possible while also reducing the setup time of each batch. This allows us to eliminate a sizable portion of each part waiting while the rest of the parts in the batch are being machined. In this paper, we propose the production scheduling problem solving using genetic and greedy algorithms with sequence dependant setup times considering the minimisation of the maximum completion time.