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Authors: Ismadi Md Badarudin 1 ; Abu Bakar Md Sultan 2 ; Md Nasir Sulaiman 2 ; Ali Mamat 2 and Mahmud Tengku Muda Mohamed 2

Affiliations: 1 Universiti Teknologi MARA, Malaysia ; 2 Universiti Putra Malaysia, Malaysia

ISBN: 978-989-8425-54-6

ISSN: 2184-4992

Keyword(s): Genetic algorithm, Specific-domain initialization, Short term memory, Shape assignment.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence and Decision Support Systems ; Enterprise Information Systems ; Scheduling and Planning ; Strategic Decision Support Systems

Abstract: The purpose in shape assignment is to find the optimal solution that combines a number of shapes with attention to full use of area. To achieve this, an analysis needs to be done several times because of the different solutions produce dissimilar number of items. Although to find the optimal solution is a certainty, the ambiguity matters and huge possible solutions require an intelligent approach to be applied. Genetic Algorithm (GA) was chosen to overcome this problem. We found that basic implementation of Genetic Algorithm produces uncertainty time and most probably contribute the longer processing time with several reasons. Thus, in order to reduce time in analysis process, we improved the Genetic Algorithm by focusing on 1) specific-domain initialization that gene values are based on the X and Y of area coordinate 2) the use of short term memory to avoid the revisit solutions occur. Through a series of experiment, the repetition of time towards obtaining the optimal result using basic GA (BGA) and improved GA (IGA) gradually increase when size of area of combined shapes raise. Using the same datasets, however, the BGA shows more repetition number than IGA indicates that IGA spent less computation time. (More)

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Paper citation in several formats:
Md Badarudin, I.; Md Sultan, A.; Sulaiman, M.; Mamat, A. and Tengku Muda Mohamed, M. (2011). AN IMPROVED GENETIC ALGORITHM WITH GENE VALUE REPRESENTATION AND SHORT TERM MEMORY FOR SHAPE ASSIGNMENT PROBLEM.In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8425-54-6, ISSN 2184-4992, pages 178-183. DOI: 10.5220/0003493601780183

@conference{iceis11,
author={Ismadi Md Badarudin. and Abu Bakar Md Sultan. and Md Nasir Sulaiman. and Ali Mamat. and Mahmud Tengku Muda Mohamed.},
title={AN IMPROVED GENETIC ALGORITHM WITH GENE VALUE REPRESENTATION AND SHORT TERM MEMORY FOR SHAPE ASSIGNMENT PROBLEM},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2011},
pages={178-183},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003493601780183},
isbn={978-989-8425-54-6},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - AN IMPROVED GENETIC ALGORITHM WITH GENE VALUE REPRESENTATION AND SHORT TERM MEMORY FOR SHAPE ASSIGNMENT PROBLEM
SN - 978-989-8425-54-6
AU - Md Badarudin, I.
AU - Md Sultan, A.
AU - Sulaiman, M.
AU - Mamat, A.
AU - Tengku Muda Mohamed, M.
PY - 2011
SP - 178
EP - 183
DO - 10.5220/0003493601780183

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