Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

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 Flexible Job Shop Problem on Multi-GPU

We propose the new framework of the distributed tabu search metaheuristic designed to be executed using a multi-GPU cluster, i.e. cluster of nodes equipped with GPU computing units. We propose a hybrid single-walk parallelization of the tabu search, where hybridization consists in examining a number of solutions from a neighborhood concurrently by several GPUs (multi-GPU). The methodology is de...

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...

A Metaheuristic Hybridization Within a Holonic Multiagent Model for the Flexible Job Shop Problem

solving flexible job-shop scheduling problem using hybrid algorithm based on gravitational search algorithm and particle swarm optimization

job shop scheduling problem has significant importance in many researchingfields such as production management and programming and also combinedoptimizing. job shop scheduling problem includes two sub-problems: machineassignment and sequence operation performing. in this paper combination ofparticle swarm optimization algorithm (pso) and gravitational search algorithm(gsa) have been presented f...

A Novel Hybrid Method for Solving Flexible Job-Shop Scheduling Problem

For the purpose of solving the flexible job-shop scheduling problem (FJSP), an improved quantum genetic algorithm based on earliness/tardiness penalty coefficient is proposed in this paper. For minimizing the completion time and the job-shop cost, a simulation model was established firstly. Next, according to the characteristics of the due in production, a double penalty coefficient was designe...