This paper presents a new genetic algorithm (GA) for solving job shop scheduling (JSS) problem, in which a two-dimensional chromosome is used to represent individuals. Classical JSS problem is formulated in a more realistic and general way in which the expected arrival time for each job and machine availability for each machine are also taken into account. This formulation also allows solving special cases of returning tasks, in which a job can have more than one task allocated for a specific machine. Through a case study, the performance of the developed GA in solving generalised classic JSS problem is evaluated and presented.
|Title of host publication||International Conference on Advances in Mechanical Engineering (ICAME'15)|
|Number of pages||6|
|Publication status||Published - 1 May 2015|
- classical job shop scheduling
- generalised job shop scheduling
- genetic algorithm
Algabasi, A., & Maheri, A. (2015). A genetic algorithm for solving classical job shop scheduling problems. In International Conference on Advances in Mechanical Engineering (ICAME'15) (pp. 1-6) http://nrl.northumbria.ac.uk/22520/1/JSS_Final.pdf