Applying Population Based ACO to Dynamic Optimization Problems
ANTS '02 Proceedings of the Third International Workshop on Ant Algorithms
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
Designing evolutionary algorithms for dynamic optimization problems
Advances in evolutionary computing
Soft Computing - A Fusion of Foundations, Methodologies and Applications
Adaptive particle swarm optimization: detection and response to dynamic systems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
The differential ant-stigmergy algorithm applied to dynamic optimization problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A dynamic artificial immune algorithm applied to challenging benchmarking problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Evolutionary programming with ensemble of explicit memories for dynamic optimization
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A diversity-guided particle swarm optimizer for dynamic environments
LSMS'07 Proceedings of the Life system modeling and simulation 2007 international conference on Bio-Inspired computational intelligence and applications
Compound particle swarm optimization in dynamic environments
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Particle swarm optimization with composite particles in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Multiswarms, exclusion, and anti-convergence in dynamic environments
IEEE Transactions on Evolutionary Computation
A hierarchical particle swarm optimizer and its adaptive variant
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
| Hi-index | 0.00 |
Dynamic optimization is a challenging problem to the classic particle swarm optimization algorithms, it requires the optimizer not only to find the global optimal solution under a specific fitness landscape but also to track the trajectory of changing optima. This paper investigates a composite particle swarm optimizer, which presents a novel version of interactions among particles, to address dynamic optimization problems. A new composite particle generation approach based on the ''fittest-oriented'' principle is proposed, it creates each composite particle by one fitter particle from the swarm and other two particles randomly generated in its neighborhoods. In order to integrate valuable information for searching the changed optima, we introduce a scatter factor into the velocity-anisotropic reflection (VAR) scheme and a ''fitness-and-distance'' based pioneer particle identification (PPI) method. In addition, the composite particles interact with other particles in the swarm using an integral movement strategy, which aims to enhance the diversity of the swarm. Based on the experimental results in static landscapes, a hyper-reflection mechanism is introduced to enhance the efficiency of the VAR operator. Experimental results on the effect of the introduced schemes and user-specified parameters on DF1 problem provides a guideline for setting the involved parameters. Experimental comparisons with other state-of-art PSO variants and evolutionary computation algorithms on DF1 functions together with a suite of DOPs generated from the generalized dynamic benchmark generator (GDBG), which were used for the 2009 Competition on Evolutionary Computation in Dynamic and Uncertain Environments (ECiDUE), are also provided.