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Publication Index: ScopusSubject: genetic algorithms

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Now showing 1 - 3 of 3
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    Article
    Citation - WoS: 12
    Citation - Scopus: 15
    Discrete Parameter-Nonlinear Constrained Optimisation of a Gear Train Using Genetic Algorithms
    (inderscience Enterprises Ltd, 2005) Dolen, M.; Kaplan, H.; Seireg, A.
    This paper investigates the optimal design of a four-stage gear train using genetic algorithms. Five different genetic encoding schemes, which incorporate various heuristic search techniques, are proposed to deal with the most critical constraints of the problem. The fitness criterion used by all genetic algorithms includes a merit function for minimising the size of the gearbox. The results show improvement in the design merit over previous approaches without reliance on the designer's interaction to avoid geometric constraint violations and facilitate the convergence.
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    Citation - WoS: 7
    Citation - Scopus: 10
    Optimizing the Performance of Single-Mode Laser Diode System Using Genetic Algorithm
    (Elsevier Sci Ltd, 2004) Aydin, E; Aydın, Elif; Yildirim, R; Aydın, Elif; Department of Electrical & Electronics Engineering; Department of Electrical & Electronics Engineering
    In this correspondence, micro-genetic algorithm (MGA) application results for optimizing the performance of electronic feedback of a laser diode are presented. The goal of optimization is to find the maximum bandwidth of the laser diode with electronic feedback used in fiber optic digital communication. A numerical analysis of the system theory of the single-mode laser diode to obtain numerical results of the gain, the Pulse response, and the harmonic distortion for electronic feedback is also presented. The dependence of the system gain on the feedback gain and delay is examined. The Pulse response is studied and it is shown that a transmission rate over 1 Gbyte/s can be achieved. (C) 2003 Elsevier Ltd. All rights reserved.
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    Article
    Citation - WoS: 11
    Citation - Scopus: 13
    An Evolutionary Approach for the Target Allocation Problem
    (Palgrave Publishers Ltd, 2003) Erdem, E; Ozdemirel, NE
    We propose an evolutionary approach for target allocation in tactical level land combat. The purpose is to assign friendly military units to enemy units such that the total weapon effectiveness used is minimised while the attrition goals set for the enemy units are satisfied. A repair algorithm is developed to ensure feasibility with respect to the attrition goal constraints. A tightness measure is devised to determine the population size of the genetic algorithm as a function of constraint tightness. Also, a local improvement algorithm is used to further improve the solution quality. Experimental results indicate that the genetic algorithm can find solutions with acceptable quality in reasonable computation time. Although the approach is developed for the target allocation problem, it can be adapted for other assignment problems.