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
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.
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