<p><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">Differential evolution, termed DE, is a novel and rapidly developed evolution computation in recent year</span><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: 新細明體; mso-ansi-language: EN-US; mso-fareast-language: ZH-TW; mso-bidi-language: AR-SA; mso-fareast-theme-font: minor-fareast;" lang="EN-US"><span class="msoIns"><ins datetime="2010-07-03T15:44" cite="mailto:saygrace"><span style="text-decoration: underline;"><span style="color: #008080;">s</span></span></ins></span></span><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">. There are some advantages of DE, including simple structure, easy use and rapid convergence speed. Besides, DE can be also applied on </span><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: 新細明體; mso-ansi-language: EN-US; mso-fareast-language: ZH-TW; mso-bidi-language: AR-SA; mso-fareast-theme-font: minor-fareast;" lang="EN-US">the </span><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">complex optimization problem. However, there are some </span><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: 新細明體; mso-ansi-language: EN-US; mso-fareast-language: ZH-TW; mso-bidi-language: AR-SA; mso-fareast-theme-font: minor-fareast;" lang="EN-US">issues</span><span style="font-family: "Times New Roman","serif"; font-size: 10pt; mso-fareast-font-family: SimSun; mso-ansi-language: EN-US; mso-fareast-language: EN-US; mso-bidi-language: AR-SA;" lang="EN-US">, such as premature convergence and stagnation, remaining in DE algorithm. To overcome those disadvantages, a different method was proposed, named CO-DE, by combining with a simple co-evolutionary model and reset mechanism. Thus, CO-DE can maintain appropriate swarm diversity and reduce the premature convergence. On the other hand, a reset mechanism was set to avoid the particle stagnates, which can further improve the performance of differential evolution. The proposed model can be now successfully applied with some well-known benchmark functions.</span></p><span style="font-family: "Times New Roman","serif&...
The reaction of sodium propargyloxide (II) with hexachlorocyclotriphosphazene (I) leads to the propargyloxy derivatives (III), (IV), and (V) depending on the stoichiometric ratio.
Differential evolution, termed DE, is a novel and rapidly developed evolution computation in recent year. There are some advantages of DE, including simple structure, easy use and rapid convergence speed. Besides, DE can be also applied on complex optimization problem. However, there are some problems, such as premature convergence and stagnation, remaining in DE algorithm. To overcome those disadvantages, a different method was proposed, named CO-DE, by combining with a simple co-evolutionary model and reset mechanism. Thus, CO-DE can maintain appropriate swarm diversity and reduce the premature convergence. On the other hand, a reset mechanism was set to avoid the particle stagnates, which can further improve the performance of differential evolution. The proposed model can be now successfully applied with some wellknown benchmark functions. (Abstract)
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