Evolutionary and bioinspired algorithms for optimization

Throughout the second half of the last century, a set of metaheuristics inspired by evolution and collective intelligence appeared that have had transcendent repercussions in the field of optimization; they are evolutionary algorithms, ant colony optimization (ACO) and particle swarm optimization (PSO). The success of these bioinspired optimization techniques has led, at present, to a growing interest in discovering other strategies inherent in living beings whose computational implementation can bring benefits in the field of optimization and, therefore, a great wave of new approaches is being produced that constitute what we could call the second generation of bioinspired algorithms. They include artificial bee colony (ABC), biogeography-based optimization, and bacterial foraging optimization.

The objective of the line “#CI – Evolutionary and bioinspired algorithms for optimization” is the study and development of bioinspired algorithms for: (1) Improve their behavior when they tackle optimization problems in continuous domains and (2) Apply and adapt them to solve specific combinatorial optimization problems, such as those related to interventions in complex networks, optimal organization of hospitals, etc.

Responsible: Manuel Lozano Márquez

Investigadores relacionados:

Letra:

  Name Email Area Cat.
Sánchez López, Ana María amlopez@ug@d1R_7Hr.es Data Science and Big Data Area PhD
Ortíz García, Andrés aortiz@ic.umKdqy9_5VOa.es DaSCI Technology Applications Area PhD
Casillas Barranquero, Jorge casillasmgDp81Mj@decsai.ugr.es Data Science and Big Data Area PhD
García Martínez, Carlos cgarciaSB@XvLI@uco.es Data Science and Big Data Area PhD
Molina Cabrera, Daniel dmolina@dec6YViBqqrgqsai.ugr.es Data Science and Big Data Area PhD
Rodríguez Díaz, Francisco Javier fjrodriguez@decsai.w_m03Augr.es Computational Intelligence Area PhD
Herrera Triguero, Francisco herrera@decsai.uqb@40WmEYovgr.es DaSCI Technology Applications Area, Data Science and Big Data Area, Computational Intelligence Area PhD
Benítez Sánchez, José Manuel J.M.BenitezfoP9YtZ@decsai.ugr.es Data Science and Big Data Area, Computational Intelligence Area PhD
Giráldez Crú, Jesús jgiraldez@ugr.k0QdQNCSKes DaSCI Technology Applications Area PhD - Juan de la Cierva
Cano de Amo, José Ramón jrcano@ujdD7h8sUuonaRaen.es Data Science and Big Data Area PhD
Chica Serrano, Manuel manuelchica@go.ucaL@dqutLgr.es DaSCI Technology Applications Area PhD - Ramón y Cajal
Gacto Colorado, María José mgacto@TLTIThnIlKjGujaen.es Data Science and Big Data Area PhD
García Arenas, María Isabel mgarenasCxDZHbDkel@ugr.es DaSCI Technology Applications Area PhD
Cordón García, Óscar ocordon@decsai.uqvRr7bRgr.es DaSCI Technology Applications Area PhD
Mesejo Santiago, Pablo pablomesejo@gBFNbC9foIQyDmail.com DaSCI Technology Applications Area PhD - Marie Curie
Castillo Valdivieso, Pedro A. pacv@ugr.qZ@39WXes DaSCI Technology Applications Area PhD
González García, Pedro pglez@ujaea9YIM2n.es Data Science and Big Data Area PhD
Villar Castro, Pedro pvillarc@utq8IEYfBcggr.es Data Science and Big Data Area PhD
Romero Zaliz, Rocío rocio@ugr.xrsE_eb1.uqes DaSCI Technology Applications Area PhD
Damas Arroyo, Sergio sdamas@ugr.DMX3PJFes DaSCI Technology Applications Area PhD
Ventura Soto, Sebastián sventura1DCQDcmU80Q@uco.es Data Science and Big Data Area PhD
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