PARALLEL GREEDY METAHEURISTIC ALGORITHM FOR SOLVING OPEN SHOP SCHEDULING PROBLEM

In a job shop each job has a fixed route that is predetermined. In practice, it often occurs that the route of the job is immaterial and up to the scheduler to decide. When the routes of the jobs are open, the model is referred to as an open shop (Pinedo, 2008). Lots types of open shop scheduling problems are known to be NP-hard. Open shop scheduling problem has received much attention due to its practical importance and lots of studies are made in the literature. In this study a parallel greedy metaheuristic algorithm (also known an artificial intelligence method) is proposed. The benchmark open shop scheduling problem is solved by proposed parallel greedy algorithm and the best results are researched.