Problem difficulty analysis for particle swarm optimization: deception and modality
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Adaptive particle swarm optimization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Fractional particle swarm optimization in multidimensional search space
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Computers & Mathematics with Applications
Evolutionary tristate PSO for strategic bidding of pumped-storage hydroelectric plant
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Integrated Learning Particle Swarm Optimizer for global optimization
Applied Soft Computing
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Multi-dimensional particle swarm optimization in dynamic environments
Expert Systems with Applications: An International Journal
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Population-based algorithm portfolios for numerical optimization
IEEE Transactions on Evolutionary Computation - Special issue on preference-based multiobjective evolutionary algorithms
Bio-inspired algorithms for autonomous deployment and localization of sensor nodes
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Polynomial modeling for time-varying systems based on a particle swarm optimization algorithm
Information Sciences: an International Journal
Information Sciences: an International Journal
Feedback learning particle swarm optimization
Applied Soft Computing
Information Sciences: an International Journal
Feedback controlled particle swarm optimization and its application in time-series prediction
Expert Systems with Applications: An International Journal
Automated lecture template generation in CORDRA-Based learning object repository
ICWL'11 Proceedings of the 10th international conference on Advances in Web-Based Learning
An intelligent augmentation of particle swarm optimization with multiple adaptive methods
Information Sciences: an International Journal
Grey particle swarm optimization
Applied Soft Computing
Diversity enhanced particle swarm optimization with neighborhood search
Information Sciences: an International Journal
LONET: An interactive search network for intelligent lecture path generation
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on agent communication, trust in multiagent systems, intelligent tutoring and coaching systems
Compact Particle Swarm Optimization
Information Sciences: an International Journal
A team-oriented approach to particle swarms
Applied Soft Computing
Particle swarm optimization with grey evolutionary analysis
Applied Soft Computing
Particle swarm optimization with increasing topology connectivity
Engineering Applications of Artificial Intelligence
Quadratic interpolation based orthogonal learning particle swarm optimization algorithm
Natural Computing: an international journal
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In this paper, we try to improve the performance of the particle swarm optimizer by incorporating the linkage concept, which is an essential mechanism in genetic algorithms, and design a new linkage identification technique called dynamic linkage discovery to address the linkage problem in real-parameter optimization problems. Dynamic linkage discovery is a costless and effective linkage recognition technique that adapts the linkage configuration by employing only the selection operator without extra judging criteria irrelevant to the objective function. Moreover, a recombination operator that utilizes the discovered linkage configuration to promote the cooperation of particle swarm optimizer and dynamic linkage discovery is accordingly developed. By integrating the particle swarm optimizer, dynamic linkage discovery, and recombination operator, we propose a new hybridization of optimization methodologies called particle swarm optimization with recombination and dynamic linkage discovery (PSO-RDL). In order to study the capability of PSO-RDL, numerical experiments were conducted on a set of benchmark functions as well as on an important real-world application. The benchmark functions used in this paper were proposed in the 2005 institute of electrical and electronics engineers congress on evolutionary computation. The experimental results on the benchmark functions indicate that PSO-RDL can provide a level of performance comparable to that given by other advanced optimization techniques. In addition to the benchmark, PSO-RDL was also used to solve the economic dispatch (ED) problem for power systems, which is a real-world problem and highly constrained. The results indicate that PSO-RDL can successfully solve the ED problem for the three-unit power system and obtain the currently known best solution for the 40-unit system.