. "Vizualizace diverzity v evolu\u010Dn\u00EDch algoritmech zalo\u017Een\u00E1 na simulaci fyzik\u00E1ln\u00EDho syst\u00E9mu"@cs . "On Visualization of Diversity in Evolutionary Algorithms Based on Simulation of Physical System" . "2"^^ . . "Ljubljana" . "RIV/68407700:21230/07:03133022!RIV08-AV0-21230___" . "978-3-901608-32-2" . "RIV/68407700:21230/07:03133022" . . "ARGESIM" . . . "2007-09-09+02:00"^^ . . "Vizualizace diverzity v evolu\u010Dn\u00EDch algoritmech zalo\u017Een\u00E1 na simulaci fyzik\u00E1ln\u00EDho syst\u00E9mu"@cs . "[481D2FF7875A]" . . . . . "Proceedings of the 6th EUROSIM Congress on Modelling and Simulation" . "Ne\u010D\u00EDslov\u00E1no" . "On Visualization of Diversity in Evolutionary Algorithms Based on Simulation of Physical System" . . "EAs can be seen as algorithms which traverse the search-space in a parallel way. Diversity is an essential aspect of each EA. The lack of diversity is a common problem. Diversity should be preserved in order to evade local extremes (premature convergence). Niching EA is based on dividing the population into separate subpopulations - it spreads the organisms effectively all over the search-space and hence making the overall population diverse. Using niching methods also requires setting of their parameters, which can be very difficult. This paper presents a novel way of diversity visualization based on physical system simulation. It is inspired by intermolecular forces and employs overall energy minimization. This minimization is done via known unconstrained optimization numerical methods. The visualization is helpful when designing and tuning niching algorithms, but it has also other uses."@en . "On Visualization of Diversity in Evolutionary Algorithms Based on Simulation of Physical System"@en . "\u0160norek, Miroslav" . . . . . "EAs can be seen as algorithms which traverse the search-space in a parallel way. Diversity is an essential aspect of each EA. The lack of diversity is a common problem. Diversity should be preserved in order to evade local extremes (premature convergence). Niching EA is based on dividing the population into separate subpopulations - it spreads the organisms effectively all over the search-space and hence making the overall population diverse. Using niching methods also requires setting of their parameters, which can be very difficult. This paper presents a novel way of diversity visualization based on physical system simulation. It is inspired by intermolecular forces and employs overall energy minimization. This minimization is done via known unconstrained optimization numerical methods. The visualization is helpful when designing and tuning niching algorithms, but it has also other uses." . "Drchal, Jan" . . "21230" . "EAs can be seen as algorithms which traverse the search-space in a parallel way. Diversity is an essential aspect of each EA. The lack of diversity is a common problem. Diversity should be preserved in order to evade local extremes (premature convergence). Niching EA is based on dividing the population into separate subpopulations - it spreads the organisms effectively all over the search-space and hence making the overall population diverse. Using niching methods also requires setting of their parameters, which can be very difficult. This paper presents a novel way of diversity visualization based on physical system simulation. It is inspired by intermolecular forces and employs overall energy minimization. This minimization is done via known unconstrained optimization numerical methods. The visualization is helpful when designing and tuning niching algorithms, but it has also other uses."@cs . . . "diversity; evolutionary algorithm; niching; visualization"@en . "439468" . "P(KJB201210701), Z(MSM6840770012)" . "2"^^ . "Vienna" . "9"^^ . "On Visualization of Diversity in Evolutionary Algorithms Based on Simulation of Physical System"@en . . .