Combination of genetic algorithm and shifting bottleneck heuristics to solve a job shop scheduling problem in wood processing company

Abstract

The scheduling problem has always been the concern of most companies in the flexible Job shop or Job shop environments because of its complexity. It is really a challenge for researchers to solve or find out the optimum solution. The lead time production at Teak Woods line in a wood processing company, a case study, faced with about 80% of orders which could not be done on time, although its capacity meet requirements. Therefore, it is very useful and necessary to set up a production scheduling model in order to reduce production time and synchronize the product’s parts through efficient modulation in an optimum sequence of jobs on the shopfloor. A combination of Genetic Algorithm and Shifting Bottleneck Heuristics was used to find out high quality solutions. It shows that the productivity increased from 2.32 m3/day to 4.3 m3/day (up 98.27%); Processing time was reduced from 3248.6 minutes to 1352.1 minutes (down 58.38%); The sync time decreased from 7554.8 minutes to 350.8 minutes (down 95.36%).