Chaos Ant Colony Optimization and Application

Gong, Wenjuan; Shoubin, Wang

doi:10.1109/icicse.2009.38

Cited by 38 publications

(24 citation statements)

References 11 publications

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“…Such simulations have revealed a A c c e p t e d M a n u s c r i p t significant increase in the quality of the obtained solution for several benchmark functions. The interested readers can refer to SA [18], GA [19], and ACO [20] to get additional information on the research carried out in this field.…”

Section: A Brief Review Of the Conducted Researchmentioning

confidence: 99%

An empirical investigation into the effects of chaos on different types of evolutionary crossover operators for efficient global search in complicated landscapes

Emami

Mozaffari

Azad

et al. 2014

International Journal of Computer Mathematics

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In this study, a comprehensive empirical test is conducted to analyze the effects of two well-known chaotic maps, namely sinusoidal and logistic maps, on the efficacy of double Pareto crossover (DPX), Laplace crossover (LX) and simulated binary crossover (SBX) operators for the global optimization of continuous problems. To do so, 13 well-known numerical benchmark problems in three distinctive dimensions, namely 50D, 100D and 200D, are considered and the genetic algorithm (GA) with simple version and chaos enhanced versions of the mentioned crossover operators are utilized for optimizing these functions. Furthermore, a time complexity analysis is conducted to find out the impact of hybridizing the chaos and the evolutionary operators on the computational complexity of GA. The results of the experimental analysis provide us with fruitful information regarding the scalability, computational complexity and exploration/exploitation capability of the considered rival optimization algorithms, as well as, demonstrate the efficacy of chaos-evolutionary computing for numerical continuous optimizations.

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Section: A Brief Review Of the Conducted Researchmentioning

confidence: 99%

An empirical investigation into the effects of chaos on different types of evolutionary crossover operators for efficient global search in complicated landscapes

Emami

Mozaffari

Azad

et al. 2014

International Journal of Computer Mathematics

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“…Chaos is a deterministic, random-like process found in a nonlinear, dynamical system, which is non-period, non-converging and non-bounded. Moreover, it depends on its initial condition and parameters [10][11][12][13][14][15][16][17]. Applications of chaos has several disciplines including operations research, physics, engineering, economics, biology, philosophy and computer science [18][19][20][21][22][23][24][25].…”

Section: Chaos Theorymentioning

confidence: 99%

An Improved Flower Pollination Algorithm with Chaos

Abdel-Raouf¹,

Abdel-Baset

El-Henawy³

2014

IJEME

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Flower pollination algorithm is a new nature-inspired algorithm, based on the characteristics of flowering plants. In this paper, a new method is developed based on the flower pollination algorithm combined with chaos theory (IFPCH) to solve definite integral. The definite integral has wide ranging applications in operation research, computer science, mathematics, mechanics, physics, and civil and mechanical engineering. Definite integral has always been useful in biostatistics to evaluate distribution functions and other quantities. Numerical simulation results show that the algorithm offers an effective way to calculate numerical value of definite integrals, and it has a high convergence rate, high accuracy and robustness.

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“…The choice of chaotic sequences is justified theoretically by their unpredictability and can be used to improve the performance of evolutionary algorithms [20]. Chaotic sequences have been used together with other algorithms such as ant colony optimization (ACO) and bee colony optimization (BCO) algorithms [21,22], imperialist competitive algorithm (ICA) [23], SA algorithm [24] GA algorithms [25] and HS algorithm [26].…”

Section: Introductionmentioning

confidence: 99%