Ant Colony Optimization - Methods and Applications by Avi Ostfeld PDF

By Avi Ostfeld

ISBN-10: 9533071575

ISBN-13: 9789533071572

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N. (2001). Optimization of Non-Stationary Problems with Evolutionary Algorithms and Dynamic Memory, PhD thesis, University of Aarhus, Department of Computer Science Ny Munkegade 8000 Aarhus C. Bendtsen, C. N. & Krink, T. (2002). Dynamic Memory Model for Non-Stationary Optimization, Congress on Evolutionary Computation, IEEE, pp. 145–150. pd f Blackwell, T. M. (2003). Particle Swarms and Population Diversity I: Analysis, in J. ), GECCO Workshop on Evolutionary Algorithms for Dynamic Optimization Problems, pp.

The fuzzy controller includes double inputs, the error in the ship heading ( Δψ ( k ) ) and the change in that error ( γ ( k ) ). Every input variable is fuzzied into 11 triangular membership functions; thus form 121 pieces of rules. The output of the fuzzy controller is the rudder input ( δ ). We want the tanker heading to track the reference input heading ψ r . 1sec. From manipulated index standpoints, it satisfied the index of 15000tdw tanker [13], a fuzzy closed-loop controlling system is designed with fuzzy rule base from experience.

To this aim, we first show a useful property of the algorithm MMAS. If xb (0) = y ∈ L k and τmax < 1, then exists a deterministic time t∗ , independent from the initial pheromone, such that, for any time t > t∗ where xb (t) is unchanged, the pheromone τ (t) is constant and equal to τ (t∗ ) = τ ∗ (y), where τij∗ (y) = τmax for any arc (i, j) belongs to y, and τij∗ (y) = τmin otherwise. The time t∗ is given by t∗ = max{t1 , t2 }, where t1 = log τmin − log τmax log(1 − ρ) , and t2 = log(1 − τmax ) − log (1 − τ min ) .

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Ant Colony Optimization - Methods and Applications by Avi Ostfeld

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