Fundamentals of queueing theory (2nd ed.).
Fundamentals of queueing theory (2nd ed.).
GENITOR II.: a distributed genetic algorithm
Journal of Experimental & Theoretical Artificial Intelligence
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Efficient reinforcement learning through symbiotic evolution
Machine Learning - Special issue on reinforcement learning
New ideas in optimization
Numerical Optimization of Computer Models
Numerical Optimization of Computer Models
Artficial Immune Systems and Their Applications
Artficial Immune Systems and Their Applications
Evolutionary Optimization
Journal of Global Optimization
Evolutionary Optimization of Yagi-Uda Antennas
ICES '01 Proceedings of the 4th International Conference on Evolvable Systems: From Biology to Hardware
Distributed Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
Co-evolutionary Constraint Satisfaction
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Ant Colony Optimization
Cooperative Coevolution: An Architecture for Evolving Coadapted Subcomponents
Evolutionary Computation
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
Comparing a coevolutionary genetic algorithm for multiobjective optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Search-intensive concept induction
Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
Robust optimization by means of vegetative reproduction
ICAIS'11 Proceedings of the Second international conference on Adaptive and intelligent systems
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This paper proposes a new individual based optimization algorithm, which is inspired from asexual reproduction known as a remarkable biological phenomenon, called as Asexual Reproduction Optimization (ARO). ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, each individual produces an offspring called bud through a reproduction mechanism; thereafter parent and its offspring compete according to a performance index obtained from the underlying objective function of the given optimization problem. This process leads to the fitter individual. ARO's adaptive search ability and its strong and weak points are described in this paper. Furthermore, the ARO convergence to the global optimum is mathematically analyzed. To approve the effectiveness of the ARO performance, it is tested with several benchmark functions frequently used in the area of optimization. Finally, the ARO performance is statistically compared with that of Particle Swarm Optimization (PSO). Results of simulation illustrate that ARO remarkably outperforms PSO.