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A new hybrid approach for dynamic continuous optimization problems

Karimi, J ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1016/j.asoc.2011.11.005
  3. Publisher: 2012
  4. Abstract:
  5. A new hybrid approach for dynamic optimization problems with continuous search spaces is presented. The proposed approach hybridizes efficient features of the particle swarm optimization in tracking dynamic changes with a new evolutionary procedure. In the proposed dynamic hybrid PSO (DHPSO) algorithm, the swarm size is varied in a self-regulatory manner. Inspired from the microbial life, the particles can reproduce infants and the old ones die. The infants are especially reproduced by high potential particles and located near the local optimum points, using the quadratic interpolation method. The algorithm is adapted to perform in continuous search spaces, utilizing continuous movement of the particles and using Euclidian norm to define the neighborhood in the reproduction procedure. The performance of the new proposed approach is tested against various benchmark problems and compared with those of some other heuristic optimization algorithms. In this regard, different types of dynamic environments including periodic, linear and random changes are taken with different performance metrics such as real-time error, offline performance and offline error. The results indicate a desirable better efficiency of the new algorithm over the existing ones
  6. Keywords:
  7. Dynamic optimization ; Particle swarm optimization ; Bench-mark problems ; Continuous optimization problems ; Dynamic changes ; Dynamic environments ; Dynamic optimization problems ; Heuristic optimization ; High potential ; Hybrid approach ; Hybrid PSO ; Local optima ; Microbial life ; Off-line performance ; Offline ; Performance metrics ; Quadratic interpolation ; Reproduction ; Search spaces ; Swarm size ; Benchmarking ; Heuristic algorithms ; Interpolation ; Particle swarm optimization (PSO)
  8. Source: Applied Soft Computing Journal ; Volume 12, Issue 3 , 2012 , Pages 1158-1167 ; 15684946 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S1568494611004297