Title :
On solving rectangle bin packing problems using genetic algorithms
Author :
Hwang, Shim-Miin ; Kao, Cheng-Yan ; Horng, Jorng-Tzong
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Taiwan Univ., Taipei, Taiwan
Abstract :
This paper presents an application of genetic algorithms in solving rectangle bin packing problems which belong to the class of NP-hard optimization problems. There are three versions of rectangle bin packing problems to be discussed in this paper: the first version is to minimize the packing area, the second version is to minimize the height of a strip packing, and the final version is to minimize the number of bins used to pack the given items. Different versions of genetic algorithms are developed to solve the three versions of problems. Among these versions of genetic algorithms, we have demonstrated two ways of applying the genetic algorithms, either to solve the problem directly or to tune an existing, heuristic algorithm so that the performance is improved, Experimental results are compared to well-known packing heuristics FFDH and HFF. From these results, we know that both methods can be useful in practice
Keywords :
computational complexity; genetic algorithms; geometry; heuristic programming; minimisation; operations research; NP-hard optimization; bin usage minimization; genetic algorithms; heuristic algorithm; packing area minimization; rectangle bin packing problems; strip packing height minimization; Application software; Approximation algorithms; Computer science; Genetic algorithms; Genetic engineering; Genetic mutations; Heuristic algorithms; Machine learning; Machine learning algorithms; Strips;
Conference_Titel :
Systems, Man, and Cybernetics, 1994. Humans, Information and Technology., 1994 IEEE International Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2129-4
DOI :
10.1109/ICSMC.1994.400073