An adaptable scheduling algorithm for flexible flow lines
Operations Research
Fast parallel heuristics for the job shop scheduling problem
Computers and Operations Research
Sequential and Parallel Path-Relinking Algorithms for the Quadratic Assignment Problem
IEEE Intelligent Systems
Parallel Metaheuristics: A New Class of Algorithms
Parallel Metaheuristics: A New Class of Algorithms
Solving the flow shop problem by parallel programming
Journal of Parallel and Distributed Computing
Parallel Simulated Annealing for the Job Shop Scheduling Problem
ICCS '09 Proceedings of the 9th International Conference on Computational Science: Part I
Solving flexible flow-shop problem with a hybrid genetic algorithm and data mining: A fuzzy approach
Expert Systems with Applications: An International Journal
On single-walk parallelization of the job shop problem solving algorithms
Computers and Operations Research
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The paper deals with the parallel variant of the scheduling algorithm dedicated to the hybrid flow shop problem. The problem derives from practice of automated manufacturing lines, e.g. for printed packages. The overall goal is to design a new algorithm which merges the performance of the best known sequential approach with the efficient exploitation of parallel calculation environments. In order to fulfill the above aim, there are two methods proposed in this paper: the original fast method of parallel calculation of the criterion function and the local neighborhood parallel search method embedded in the tabu search approach. The theoretical analysis, as well as the original implementation, with the use of vector processing instructions SSE2 supported by suitable data organization, are presented below. Numerical properties of the proposed algorithm are empirically verified on the multi-core processor.