Solving the Rectangular Packing Problem by an Adaptive GA Based on Sequence-Pair

A
ASP-DAC
1999
Asia and South Pacific Design Automation Conference 1999 (ASP-DAC'99)
Abstract - Solving the Rectangular Packing Problem by an Adaptive GA Based on Sequence-Pair

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Asia and South Pacific Design Automation Conference 1999 (ASP-DAC'99)

Wanchai, Hong Kong

January 18-January 21

ISBN: 0-7803-5012-X

	ASCII Text	x
	Koichi Hatta, Shin'ichi Wakabayashi, Tetsushi Koide, "Solving the Rectangular Packing Problem by an Adaptive GA Based on Sequence-Pair," Asia and South Pacific Design Automation Conference, pp. 181, Asia and South Pacific Design Automation Conference 1999 (ASP-DAC'99), 1999.

	BibTex	x
	@article{ 10.1109/ASPDAC.1999.759990, author = {Koichi Hatta and Shin'ichi Wakabayashi and Tetsushi Koide}, title = {Solving the Rectangular Packing Problem by an Adaptive GA Based on Sequence-Pair}, journal ={Asia and South Pacific Design Automation Conference}, volume = {0}, year = {1999}, isbn = {0-7803-5012-X}, pages = {181}, doi = {http://doi.ieeecomputersociety.org/10.1109/ASPDAC.1999.759990}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Asia and South Pacific Design Automation Conference TI - Solving the Rectangular Packing Problem by an Adaptive GA Based on Sequence-Pair SN - 0-7803-5012-X SP EP A1 - Koichi Hatta, A1 - Shin'ichi Wakabayashi, A1 - Tetsushi Koide, PY - 1999 KW - null VL - 0 JA - Asia and South Pacific Design Automation Conference ER -

Koichi Hatta, Hiroshima University, Japan

Shin'ichi Wakabayashi, Hiroshima University, Japan

Tetsushi Koide, Hiroshima University, Japan

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ASPDAC.1999.759990

In this paper, we propose a genetic algorithm (GA) to solve the rectangular packing problem(RP), in which the sequence-pair representation is adopted as the coding scheme of each chromosome. New genetic operators for RP is presented to explore the search space efficiently. The proposed GA has an adaptive strategy which dynamically selects an appropriate genetic operator during the GA execution depending on the state of an individual. Experimental results show the effectiveness of our adaptive genetic algorithm compared to simulated annealing (SA).

Citation:

Koichi Hatta, Shin'ichi Wakabayashi, Tetsushi Koide, "Solving the Rectangular Packing Problem by an Adaptive GA Based on Sequence-Pair," asp-dac, pp.181, Asia and South Pacific Design Automation Conference 1999 (ASP-DAC'99), 1999

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