http://epso.inesctec.pt These are the search results for the query, showing results 1 to 15. http://epso.inesctec.pt/epso-code-c/gnu-general-public-license-gpl-3 This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. If you use EPSO in a work that leads to a scientific publication, we would appreciate it if you would kindly cite EPSO in your manuscript: V. Miranda and N. Fonseca, "EPSO ‐ best‐of‐two‐worlds meta‐heuristic applied to power system problems", IEEE WCCI, Proceedings of the 2002 Congress on Evolutionary Computation CEC'02, 12‐17 May 2002; DOI: 10.1109/CEC.2002.1004393 No publisher vmiranda 2021-04-24T19:06:32Z File http://epso.inesctec.pt/research-team/naing-win-oo This researcher applied early EPSO versions in the problem of modelling retail energy markets in an intelligent agent platform and showed that EPSO performed better than competitor algorithms No publisher vmiranda 2018-12-16T13:42:01Z Image http://epso.inesctec.pt/deepso/MovEq2.jpg No publisher vmiranda 2015-07-30T14:48:54Z Image http://epso.inesctec.pt/deepso/Mov_eq.jpg No publisher vmiranda 2015-07-30T14:43:34Z Image http://epso.inesctec.pt/deepso/deepso-publications/pmaps-2014-deepso-and-facts-location This paper presents a new stochastic programming model for PAR/PST definition and location in a network with a high penetration of wind power, with probabilistic representation, to maximize wind power penetration. It also presents a new optimization meta-heuristic, denoted DEEPSO, which is a variant of EPSO, the Evolutionary Particle Swarm Optimization method, borrowing the concept of rough gradient from Differential Evolution algorithms. A test case is solved in an IEEE test system. The performance of DEEPSO is shown to be superior to EPSO in this complex problem. No publisher vmiranda 2015-07-29T16:41:32Z File http://epso.inesctec.pt/deepso/Schoolofjellyfish.jpg No publisher vmiranda 2014-04-14T12:48:04Z Image http://epso.inesctec.pt/deepso/deepso-basics DEEPSO does not use the particle best ancestor but a recombination of the best ancestors of each particle No publisher vmiranda 2015-07-30T14:48:27Z Page http://epso.inesctec.pt/deepso/deepso-epso-with-a-touch-of-de A description of a highly performant variant of EPSO - borrowing concepts from Differential Evolution (DE) yet remaining with a pure EPSO logic. No publisher vmiranda 2014-04-14T12:47:30Z Page http://epso.inesctec.pt/deepso A description of a highly performant variant of EPSO - borrowing concepts from Differential Evolution (DE) yet remaining with a pure EPSO logic. No publisher vmiranda 2014-03-30T22:23:19Z Folder http://epso.inesctec.pt/deepso/deepso-publications Papers describing the applicarion of DEEPSO No publisher vmiranda 2014-03-30T22:06:51Z Folder http://epso.inesctec.pt/deepso/deepso-publications/brics-cci-porto-de-galinhas-pe-brazil-8-11-september-2013-copyright-ieee This paper explores, with numerical case studies, the performance of an optimization algorithm that is a variant of EPSO, the Evolutionary Particle Swarm Optimization method. EPSO is already a hybrid approach that may be seen as a PSO with self-adaptive weights or an Evolutionary Programming approach with a self-adaptive recombination operator. The new hybrid DEEPSO retains the self-adaptive properties of EPSO but borrows the concept of rough gradient from Differential Evolution algorithms. The performance of DEEPSO is compared to a well-performing EPSO algorithm in the optimization of problems of the fixed cost type, showing consistently better results in the cases presented. No publisher vmiranda 2014-03-30T21:59:42Z File http://epso.inesctec.pt/deepso/deepso-publications/ieee-swarm-optimization-sysmposium-indianapolis-indiana-usa-may-2006 This paper presents some new ideas to improve the performance of EPSO (Evolutionary Particle Swarm Optimization). It discusses a Stochastic Star communication scheme and differential dEPSO. The paper presents results in a didactic Unit Commitment/Generator Scheduling Power System problem and results of a competition among algorithms in an intelligent agent platform for Energy Retail Market simulation where EPSO comes out as the winner algorithm. [this is not DEEPSO but a preliminary hybrid of DE with EPSO - interesting, though] No publisher vmiranda 2014-03-30T21:59:42Z File http://epso.inesctec.pt/deepso/Mov2.jpg No publisher vmiranda 2014-03-30T22:16:49Z Image http://epso.inesctec.pt/deepso/bg.jpg No publisher vmiranda 2014-03-30T22:10:01Z Image http://epso.inesctec.pt/deepso/mutbG.jpg No publisher vmiranda 2014-03-30T22:10:01Z Image