Displaying similar documents to “An Electromagnetism Metaheuristic for the Uncapacitated Multiple Allocation Hub Location Problem”

Algorithmic Background of the Host Recommendation in the Adaptive Distributed Multimedia Server

Szkaliczki, Tibor, Goldschmidt, Balázs, Böszörmenyi, Laszlo (2007)

Serdica Journal of Computing

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Partial support of the Hungarian State Eötvös Scholarship, the Hungarian National Science Fund (Grant No. OTKA 42559 and 42706) and the Mobile Innovation Center, Hungary is gratefully acknowledged. In a distributed server architecture an obvious question is where to deploy the components. Host recommendation, which gives the answer, faces problems such as server selection, host deployment and, in case of multimedia servers, video replication. It is especially relevant for the...

A model and an algorithm for the grouping problem in telecom networks.

F. García, K. D. Hackbarth (1991)

Qüestiió

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This paper deals with the so called grouping problem which arises in telecommunication network optimization when transmission equipment with a certain hierarchy is used. It is shown how this problem is embedded in the complete scheme of network optimization and a general combinatorial model is developed to derive afterwards a solution procedure. The implementation of this procedure forms part of a software tool for the complete problem of transmission network planning. Some results deriving...

A neural-network controlled dynamic evolutionary scheme for global molecular geometry optimization

Anna Styrcz, Janusz Mrozek, Grzegorz Mazur (2011)

International Journal of Applied Mathematics and Computer Science

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A novel, neural network controlled, dynamic evolutionary algorithm is proposed for the purposes of molecular geometry optimization. The approach is tested for selected model molecules and some molecular systems of importance in biochemistry. The new algorithm is shown to compare favorably with the standard, statically parametrized memetic algorithm.

An approach based on the use of the ant system to design combinational logic circuits.

Benito Mendoza García, Carlos A. Coello Coello (2002)

Mathware and Soft Computing

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In this paper we report the first attempt to design combinational logic circuits using the ant system. In order to design circuits, a measure of quality improvement in partially built circuits is introduced and a cost metric (based on the number of gates) is adopted in order to optimize the feasible circuits generated. The approach is compared to a genetic algorithm and to a human designer using several examples and the sensitivity of the algorithm to its parameters is studied using...

A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers

Mineichi Kudo, Jack Sklansky (1998)

Kybernetika

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Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results show that the sequential floating algorithms promises for...

Solving the Task Assignment Problem with a Variable Neighborhood Search

Kratica, Jozef, Savić, Aleksandar, Filipović, Vladimir, Milanović, Marija (2010)

Serdica Journal of Computing

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In this paper a variable neighborhood search (VNS) approach for the task assignment problem (TAP) is considered. An appropriate neighborhood scheme along with a shaking operator and local search procedure are constructed specifically for this problem. The computational results are presented for the instances from the literature, and compared to optimal solutions obtained by the CPLEX solver and heuristic solutions generated by the genetic algorithm. It can be seen that the proposed...

On Solving the Maximum Betweenness Problem Using Genetic Algorithms

Savić, Aleksandar (2009)

Serdica Journal of Computing

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In this paper a genetic algorithm (GA) is applied on Maximum Betweennes Problem (MBP). The maximum of the objective function is obtained by finding a permutation which satisfies a maximal number of betweenness constraints. Every permutation considered is genetically coded with an integer representation. Standard operators are used in the GA. Instances in the experimental results are randomly generated. For smaller dimensions, optimal solutions of MBP are obtained by total enumeration. For...