Title :
Logistic regression for parameter tuning on an evolutionary algorithm
Author :
Ramos, Iloneide C O ; Goldbarg, Marco C. ; Goldbarg, Elizabeth G. ; Neto, Adrião D Dória
Author_Institution :
Dept. of Stat., UFRN, Natal, Brazil
Abstract :
The investigation of the parameters for which algorithms have their best performance is crucial when working with metaheuristics. This paper proposes the utilization of logistic regression, a statistical tool, for parameter tuning of an evolutionary algorithm called ProtoG. To illustrate the ideas proposed in this work, the algorithm is applied to the traveling salesman problem.
Keywords :
evolutionary computation; heuristic programming; logistics; regression analysis; travelling salesman problems; ProtoG; evolutionary algorithm; logistic regression; metaheuristics; parameter tuning; statistical tool; traveling salesman problem; Algorithm design and analysis; Biological cells; Evolutionary computation; Graphics; Logistics; Performance analysis; Statistical analysis; Statistics; Testing; Traveling salesman problems;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1554808
