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Dynamic domain transformation resource scheduling approach: water irrigation scheduling for urban farming

IAES International Journal of Artificial Intelligence · Vol. 11 No. 2 (2022) · hlm. 624–631

DOI
10.11591/ijai.v11.i2.pp624-631
ISSN
2252-8938, 2089-4872
Terbit
2022-06-01
Penerbit
Institute of Advanced Engineering and Science
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Scheduling resources under limited resources using tailored approaches can be done successfully. However, there are situations and problems that require a schedule to handle uncertainties dynamically. The changes in the environment could lead to a non-optimal schedule, which could lead to the wastage of resources. The infeasible schedule could also be an outcome of changes that would render the schedule obsolete, and a new schedule must be generated. The majority of the scheduling problems are solved by a heuristic approach that utilizes a random number generator, thus the outcome is not guaranteed to be optimal. Domain transformation approach (DTA) is a scheduling methodology that has confirmed its expressive power in producing feasible and good quality schedules through avoidance of randomness elements as highly used in heuristic approaches. DTA has been employed in this study to solve the water irrigation scheduling for urban farming. The proposed model was tested on three different datasets. It was observed that the costs obtained on all datasets without utilizing the dynamic DTA are higher in all instances, which indicates that the solution produced by DTA is of higher quality. Thus, dynamic DTA is a more effective way of scheduling resources with considering ad-hoc changes.

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  • Universiti Teknologi MARA
  • Indonesia University of Education
  • Jiujiang Vocational University
  • Universiti Teknologi Petronas
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  • Organisasi berbeda
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Rekan penulisOrganisasiArtikel bersama
Nursuriati JamilUniversiti Teknologi MARA3
Raihah AminuddinUniversiti Teknologi MARA3
Lala Septem RizaIndonesia University of Education2
Khyrina Airin Fariza Abu SamahUniversiti Teknologi MARA2
Ruiyun QiuUniversiti Teknologi MARA2
Gao YoushengUniversiti Teknologi MARA2
Ang LiJiujiang Vocational University2
Rosniza RoslanUniversiti Teknologi MARA1
Amni Munira KhidirUniversiti Teknologi MARA1
Syed Mohd Zahid Syed Zainal AriffinUniversiti Teknologi MARA1
Nor Diana AhmadUniversiti Teknologi MARA1
Shahirah Mohamed HatimUniversiti Teknologi MARA1
Masurah MohamadUniversiti Teknologi MARA1
Suraya MasromUniversiti Teknologi MARA1
Abdullah Sani Abd RahmanUniversiti Teknologi Petronas1
Norhayati BaharunUniversiti Teknologi MARA1
Nor Aiza MoketarUniversiti Teknologi MARA1
Nurqueen Sayang Dinnie WirakarnainUniversiti Teknologi MARA1
Zainab OthmanUniversiti Teknologi MARA1
Shafaf IbrahimUniversiti Teknologi MARA1
Nurul Amira Mohd AliUniversiti Teknologi MARA1

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Sumber metadata: OAI-PMH (metadata jurnal) http://ijai.iaescore.com/index.php/IJAI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Dynamic domain transformation resource scheduling approach: water irrigation scheduling for urban farming</dc:title>
	<dc:creator>Megat Amerudin, Megat Nabil Irwan</dc:creator>
	<dc:creator>Abdul Rahim, Siti Khatijah Nor</dc:creator>
	<dc:creator>Omar, Nasiroh</dc:creator>
	<dc:creator>Sulaiman, Mohd Suffian</dc:creator>
	<dc:creator>Jaafar, Amir Hamzah</dc:creator>
	<dc:creator>Hamzah, Raseeda</dc:creator>
	<dc:subject xml:lang="en-US"></dc:subject>
	<dc:subject xml:lang="en-US">domain transformation; irrigation scheduling; pre-processing; resource scheduling; urban farming;</dc:subject>
	<dc:description xml:lang="en-US">Scheduling resources under limited resources using tailored approaches can be done successfully. However, there are situations and problems that require a schedule to handle uncertainties dynamically. The changes in the environment could lead to a non-optimal schedule, which could lead to the wastage of resources. The infeasible schedule could also be an outcome of changes that would render the schedule obsolete, and a new schedule must be generated. The majority of the scheduling problems are solved by a heuristic approach that utilizes a random number generator, thus the outcome is not guaranteed to be optimal. Domain transformation approach (DTA) is a scheduling methodology that has confirmed its expressive power in producing feasible and good quality schedules through avoidance of randomness elements as highly used in heuristic approaches. DTA has been employed in this study to solve the water irrigation scheduling for urban farming. The proposed model was tested on three different datasets. It was observed that the costs obtained on all datasets without utilizing the dynamic DTA are higher in all instances, which indicates that the solution produced by DTA is of higher quality. Thus, dynamic DTA is a more effective way of scheduling resources with considering ad-hoc changes.</dc:description>
	<dc:publisher xml:lang="en-US">Institute of Advanced Engineering and Science</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2022-06-01</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://ijai.iaescore.com/index.php/IJAI/article/view/21473</dc:identifier>
	<dc:identifier>10.11591/ijai.v11.i2.pp624-631</dc:identifier>
	<dc:source xml:lang="en-US">IAES International Journal of Artificial Intelligence (IJ-AI); Vol 11, No 2: June 2022; 624-631</dc:source>
	<dc:source>2252-8938</dc:source>
	<dc:source>2089-4872</dc:source>
	<dc:source>10.11591/ijai.v11.i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://ijai.iaescore.com/index.php/IJAI/article/view/21473/13363</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Institute of Advanced Engineering and Science</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>