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PL
W artykule dokonano porównania kilku wybranych algorytmów wykorzystujących elastyczny model szeregowania zadań i przedstawiono inne podejście do modyfikacji okresów zadań wykonywanych w systemie z wykorzystaniem algorytmu ewolucyjnego. Zamieszczone przykładowe wyniki symulacji ilustrują szeregowanie zadań z wykorzystaniem wcześniej wspomnianego algorytmu ewolucyjnego.
EN
In this paper comparisons of some elastic scheduling for task model and new applications of evolution algorithm are presented. At the end some results of simulations are described.
EN
The main objective of this paper is to develop an effective evolutionary algorithm (EA) for the path-assignment problem in survivable connection-oriented networks. We assume a single-link failure scenario, which is the most common and frequently reported failure event. Since the network flow is modeled as a non-bifurcated multicommodity flow, the discussed optimization problem is NP-complete. Thus, we develop an effective heuristic algorithm based on an evolutionary algorithm. The main novelty of this work is that the proposed evolutionary algorithm consists of two levels. The “high” level applies typical EA operators. The “low” level is based on the idea of a hierarchical algorithm. However, the presented approach is not a classical hierarchical algorithm. Therefore, we call the algorithm quasi-hierarchical. We present its description and the results of simulation runs over various networks.
EN
The paper presents fragment of a larger study concerning the effective methods of solving the inverse boundary value problems. The boundary value problem described here is formulated as a problem of the identification of a boundary geometry with corner points. A method using a parametric integral equations system (PIES) is proposed. PIES used in the method makes the easy modelling of the geometry with corner points possible. This effect is obtained by the application of modified splines. An evolution algorithm is used for the effective control of modifications of the boundary geometry. Some experimental tests of the efficiency of the discussed method were performed for two-dimensional inverse potential problems.
4
Content available remote An application of population-based metaheuristics to minimizing schedule makespan
EN
The paper investigates application of the three population-based metaheuristics - evolution algorithm, population learning algorithm and ant colony optimization to minimizing schedule makespan. All three approaches are briefly revieved. Their implementation to schedule makespan minimization in case of independent, non-preemptable tasks and multiple processors is described. The approach is evaluated by means of computational experiment, results of which are presented and discussed.
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