DocumentCode :
238806
Title :
Fitness level based adaptive operator selection for cutting stock problems with contiguity
Author :
Kai Zhang ; Weise, Thomas ; Jinlong Li
Author_Institution :
Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China(USTC), Hefei, China
fYear :
2014
fDate :
6-11 July 2014
Firstpage :
2539
Lastpage :
2546
Abstract :
In this article, we propose the Fitness Level based Adaptive Operator Selection (FLAOS). In FLAOS, the discovered objective values are divided into intervals, the fitness levels. A probability distribution corresponding to a fitness level describes the selection probabilities of a set of operators. An evolutionary algorithm with FLAOS is suggested to solve one-dimensional cutting stock problems (CSPs) with contiguity. These problems are bi-objective and the goals are to minimize the trim loss and to minimize the number of partially finished items. Experimental studies have been carried out to test the effectiveness of the FLAOS. The solutions found by FLAOS are better than or comparable to those solutions found by previous methods.
Keywords :
bin packing; combinatorial mathematics; evolutionary computation; minimisation; statistical distributions; CSPs; FLAOS; combinatorial optimization problems; cutting stock problem with contiguity; evolutionary algorithm; fitness level based adaptive operator selection; one-dimensional cutting stock problems; probability distribution; selection probability; trim loss minimization; Educational institutions; Genetic algorithms; Linear programming; Minimization; Probability distribution; Sociology; Statistics; AOS; cutting stock problems; fitness level;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation (CEC), 2014 IEEE Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-6626-4
Type :
conf
DOI :
10.1109/CEC.2014.6900335
Filename :
6900335
Link To Document :
بازگشت