In the paper we propose a new framework for the distributed tabu search algorithm designed to be executed with the use of a multi-GPU cluster, in which cluster of nodes are equipped with multicore GPU computing units....
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In the paper we propose a new framework for the distributed tabu search algorithm designed to be executed with the use of a multi-GPU cluster, in which cluster of nodes are equipped with multicore GPU computing units. The proposed methodology is designed specially to solve difficult discrete optimization problems, such as a flexible job shop scheduling problem, which we introduce as a case study used to analyze the efficiency of the designed synchronous algorithm.
In this paper we consider a multi-machine scheduling problem with setup times, which is determined in the literature as the flexible job shop problem. It belongs to the strongly NPcomplete complexity *** propose an al...
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In this paper we consider a multi-machine scheduling problem with setup times, which is determined in the literature as the flexible job shop problem. It belongs to the strongly NPcomplete complexity *** propose an algorithm based on the tabu search method. The new elimination criteria were used in the construction process of blocks of the critical path.
This paper concerns the domain of the multimodal transportation systems composed of buses, trains, trams and subways lines and focuses on the scheduling problems encountered in these systems. Transportation Network In...
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This paper concerns the domain of the multimodal transportation systems composed of buses, trains, trams and subways lines and focuses on the scheduling problems encountered in these systems. Transportation Network Infrastructure (TNI) can be modeled as a network of lines providing cyclic routes for particular kinds of stream-like moving transportation means. Lines are connected by common shared change stations. Depending on TNI timetabling the time of the trip of passengers following different itineraries may dramatically differ, e.g. the same distances along the north-south, and east-west directions may require different travel time. So, the mine question regards of TNI schedulability, e.g. the guarantee the same distances in arbitrarily assumed directions will require approximate traveled time. Considered timetabling problem belongs to NP-hard ones. The declarative model of TNI enabling to formulate cyclic scheduling problem in terms of the constraint satisfaction one is our main contribution. At last, the simulated results manifest the promising properties of the proposed model.
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 par...
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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 designed to solve the flexible job shop scheduling problem, diffcult problem of discrete optimization.
This paper extends the RAS-based approach to conflict resolution in multi-vehicle systems presented in Reveliotis and Roszkowska (2008). Similar to that earlier work, the employed model assumes the tesselation of the ...
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Information sharing, exchanging and archiving is the backbone of any organized activity, regardless if it is performed in the sphere of business, home or administration. Semantic Web technologies allow controlling the...
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The paper introduces accuracy boosting extension to a novel induction of fuzzy rules from raw data using Artificial Immune System methods. Accuracy boosting relies on fuzzy partition learning. The performance, in term...
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The paper introduces accuracy boosting extension to a novel induction of fuzzy rules from raw data using Artificial Immune System methods. Accuracy boosting relies on fuzzy partition learning. The performance, in terms of classification accuracy, of the proposed approach was compared with traditional classifier schemes: C4.5, Naïve Bayes, K, Meta END, JRip, and Hyper Pipes. The result accuracy of these methods are significantly lower than accuracy of fuzzy rules obtained by method presented in this study (paired t-test, P
In the paper we want to present a problem of path following for nonholonomic mobile manipulators. In our consideration we restrict ourself to doubly nonholonomic mobile manipulators. Nonholonomic constraints appear du...
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In this work we use the Fourier expansion to characterize and model many-core processor workloads for the purpose of computing accurate predictions of individual core thermal statuses. We demonstrate, that even if the...
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This paper compares two methodologically different approaches to gene set analysis applied for selection of features for sample classification based on microarray studies. We analyze competitive and self-contained met...
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