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Aranya Walairacht

dblp:53/1031 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2002
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Computational fabrication · 100%
Theoretical computer science
1 paper
Mathematical optimization · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational fabrication
sheet metal bending		 0.012001
Multi-component Genetic Algorithm for Generating Best Bending Sequence and Tool Selection in Sheet Metal Parts · ICRA 2001
Mathematical optimization
combinatorial optimization		 0.012001
Multi-component Genetic Algorithm for Generating Best Bending Sequence and Tool Selection in Sheet Metal Parts · ICRA 2001

Methods — techniques the papers use, named apart from their topics

multi-component genetic algorithm · 0.1
YearPublicationVenuePosition
2002 Preprocessor to Improve Performance of GA in Determining Bending Process for Sheet Metal Industry
Chitra Malini Thanapandi, Aranya Walairacht, Thanapandi Periasamy, Shigeyuki Ohara
 ISMIS2
2001 Multi-component Genetic Algorithm for Generating Best Bending Sequence and Tool Selection in Sheet Metal Parts
abstract
Investigates a multi-component genetic algorithm for obtaining an optimal solution to the problem of generating bending sequence and tool selection in sheet metal parts. The multi-component genetic algorithm represents three important factors that determine the feasible solution the bend sequence, punch and die to be selected. We analyze and define the problem and discuss our approach towards solving it and the ideas are being implemented and evaluated using the real part data.
Chitra Malini Thanapandi, Aranya Walairacht, Shigeyuki Ohara
 ICRA2