Parallel Metaheuristics for Shop Scheduling: enabling Industry 4.0

Metaheuristics for Group Shop Scheduling

The Group Shop Scheduling Problem (GSP) is a generalization of the classical Job Shop and Open Shop Scheduling Problems. In the GSP there are m machines and n jobs. Each job consists of a set of operations, which must be processed on specified machines without preemption. The operations of each job are partitioned into groups on which a total precedence order is given. The problem is to order t...

Parallel metaheuristics for the cyclic flow shop scheduling problem

Job Shop Scheduling with Metaheuristics for Car Workshops

For this thesis, different algorithms were created to solve the problem of Jop Shop Scheduling with a number of constraints. More specifically, the setting of a (simplified) car workshop was used: the algorithms had to assign all tasks of one day to the mechanics, taking into account minimum and maximum finish times of tasks and mechanics, the use of bridges, qualifications and the delivery and...

Parallel hybrid metaheuristics for the flexible job shop problem

A parallel approach to flexible job shop scheduling problem is presented in this paper. We propose two double-level parallel metaheuristic algorithms based on the new method of the neighborhood determination. Algorithms proposed here include two major modules: the machine selection module refer to executed sequentially, and the operation scheduling module executed in parallel. On each level a m...

Solving the continuous flow-shop scheduling problem by metaheuristics

Continuous flow-shop scheduling problems circumscribe an important class of sequencing problems in the field of production planning. The problem considered here is to find a permutation of jobs to be processed sequentially on a number of machines under the restriction that the processing of each job has to be continuous with respect to the objective of minimizing the total processing time (flow...