Genetic Algorithm for Job Shop Scheduling Problem: A Case Study
Penulis/Author
Ir. Agus Darmawan, S.T., M.S., Ph.D., IPM., ASEAN Eng. (2)
Tanggal/Date
2013
Kata Kunci/Keyword
Abstrak/Abstract
The job-shop scheduling (JSS) is a schedule
planning for low volume systems with many variations in
requirements. In job-shop scheduling problem (JSSP), there are
k operations and n jobs to be processed on m machines with a
certain objective function to be minimized. Due to complexity of
transferring work in process product, this research add
transfer time variable from one machine to another for each
different operation. Performance measures are mean flow time
and make span. In this paper we used genetic algorithm (GA)
with some modifications to deal with problem of job shop
scheduling. The result than is compared with dispatching rules
such as longest processing time, shortest processing time and
first come first serve. The numerical example showed that GA
result can outperform the other three methods.
