Εφαρμογές του αλγορίθμου της νυχτερίδας σε πολυκριτηριακά προβλήματα βελτιστοποίησης
Bat algorithm applications in multi-objective optimization problems
Γονιδάκης, Δημήτριος Κ.
Last four decades there is a high progress level in development of metaheuristics, i.e. algorithms which can be applied to NP-hard optimization problems where deterministic approaches can’t be used. Such advanced techniques are usually based on modeling of natural, biological and social behaviours. Metaheurstics such as Genetic Algorithms, Differential Evolution, Simulated Annealing, Particle Swarm Optimization, Harmony Search and Artificial Bee Colony successfully combine exploitation around a good solution and exploration of the solution space. Bat Algorithm is a very recent and efficient metaheuristic, inspired by the echolocation of microbats. It is used for solving the combined economic and emission dispatch, a very important complex optimization problem in a power generation system. Main purpose is the minimization of two conflicting objectives, the fuel cost and pollutant emission, while satisfying all operational constraints. Bat Algorithm is used for three different generating test systems and obtaining results are compared to those obtained by other algorithms.