Material flow optimisation of production planning and scheduling problem in flexible manufacturing system by real coded genetic algorithm (RCGA)

• Published in: Flexible services and manufacturing journal Vol. 31; no. 2; pp. 381 - 423
• Main Authors: Bhosale, K. C., Pawar, P. J.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2019; Springer Nature B.V
• Subjects: Completion time; Engineering; Flexible manufacturing systems; Genetic algorithms; Machines; Manufacturing; Operations Management; Operations Research/Decision Theory; Optimization; Processes; Production planning; Production scheduling; Scheduling; Real time scheduling with waiting time; Real coded genetic algorithm (RCGA); Material flow; Flexible manufacturing systems; Integrated production planning problem and scheduling problem
• ISSN: 1936-6582; 1936-6590
• DOI: 10.1007/s10696-018-9310-5

In a loading problem of flexible manufacturing system (FMS), part type selection and operations allocation are two critical problems. The total completion time of a product for the selected process plan in the system can be minimum for the loading problem. But, in a real time scheduling system, this process plan may not be optimum because of consideration of waiting time of product and machine. So, the total completion time and thereby the material flow of the selected process plan in the FMS may be high. Due to this problem an integrated approach of part type selection and an operation allocation problem i.e. production planning problem and scheduling problem is considered to optimise material flow in FMS. Loading and scheduling problems are NP-hard in nature. So, to solve complex problems like this, real coded genetic algorithm (RCGA) is used which overcomes some limitations of genetic algorithm. It is observed that, the results of optimisation using RCGA outperforms those obtained by earlier researchers.