Global Optimization by Repulsive Particle Swarm method
The traditional RPS, however, gives little scope of local search to the particles. They are guided by their past experience and the communication received from the others in the swarm. We have modified the traditional RPS method by endowing stronger (wider) local search ability to each particle. Each particle flies in its local surrounding and searches for a better solution. The domain of its search is controlled by a new parameter (nstep). This local search has no preference to gradients in any direction and resembles closely to tunneling. This added exploration capability of the particles brings the RPS method closer to what we observe in real life. However, in some cases moderately wide search (nstep=9, say; see program) works better (Mishra, 2009).
The program (source codes) provided here includes numerous test (benchmark) functions. The user may remove or retain them and add a specific subroutione to formulate the problem of interest. The user-written subroutine must be linked to the main program through SUBROUTINE FSELECT(KF,M,FTIT) and SUBROUTINE FUNC(X,M,F). The program may be compiled by a suitable FORTRAN compiler (e.g. Microsoft Fortran Compiler or force.lepsch.com or FORCE Fortran 77 compiler; note that FORCE Compilers are free downloadable), which, after compilation will yield RPS.EXE.
A typical subroutine is given here. It is also shown how the SUBROUTINE TREFETHEN is joined to SUBROUTINE FSELECT(KF,M,FTIT) and SUBROUTINE FUNC(X,M,F). The main program calls FSELECT and FUNC subroutines (and others, too).
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- Mishra, S.K. (2006) "Performance of Repulsive Particle Swarm Method in Global Optimization of Some Important Test Functions: A Fortran Program" , Social Science Research Network (SSRN), Working Papers Series, http://ssrn.com/abstract=924339 , 2006.
- Mishra, S.K. (2006) "Some New Test Functions for Global Optimization and Performance of Repulsive Particle Swarm Method", Social Science Research Network (SSRN): http://ssrn.com/abstract=927134, Working Papers Series, 2006.
- Mishra, SK (2009) "Global Optimization by Particle Swarm Method", ICFAI University Journal of Computational Mathematics, II(4), 2009, pp. 7-16.
- Simon, H.A. (1962) Models of Bounded Rationality, Cambridge Univ. Press, Cambridge, MA, 1982.
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