Mariusz Uchronski

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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(More)
We consider a metaheuristic optimization algorithm which uses single process (thread) to guide the search through the solution space. Thread performs in the cyclic way (iteratively) two main tasks: the goal function evaluation for a single solution or a set of solutions and management (solution filtering and selection, collection of history, updating). The(More)
The aim of this paper is to show how to determine the neighborhood of the complex discrete optimization problem and how to search it in the parallel environment, this being illustrated by an example of the hybrid scheduling, more precisely a flexible job shop problem. We present a parallel single-walk approach in this respect. A theoretical analysis based(More)
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(More)
Keywords: Scheduling Cyclic flow shop problem Block properties a b s t r a c t The cyclic flow show problem with machine setups is considered in this paper. It relies in producing of a set of certain elements in fixed intervals of time (cycle time). Process optimization is reduced to minimization of cycle time, i.e., the time after which the next batch of(More)