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Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 11 No. 2 (2017) · pp. 109–118

DOI
10.22146/ijccs.16631
ISSN
2460-7258, 1978-1520
Published
2017-07-31
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
Language
eng
License
creativecommons.org/licenses/by-sa/4.0

Abstract

Common practice in crowdsourced delivery services is through direct delivery. That is by dispatching direct trip to a driver nearby the origin location. The total distance can be reduced through multiple pickup and delivery by increasing the number of requests in a trip.The research implements exact algorithm to solve the consolidation problem with up to 3 requests in a trip. Greedy heuristic is performed to construct initial route based on highest savings. The result is then optimized using Ant Colony Optimization (ACO). Four scenarios are compared. A direct delivery scenarios and three multiple pickup and delivery scenarios. These include 2-consolidated delivery, 3-consolidated delivery, and 3-consolidated delivery optimized with ACO. Four parameters are used to evaluate using Analytical Hierarchical Process (AHP). These include the number of trips, total distance, total duration, and security concerns.The case study is based on Yogyakarta area for a whole day. The final route optimized with ACO shows 178 requests can be completed in 94 trips. Compared to direct delivery, consolidation can provides savings up to 20% in distance and 14% in duration. The evaluation result using AHP shows that ACO scenario is the best scenario.

Keywords

Collaboration network of the authors

22 authors · 26 co-authorship links · 5 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Gadjah Mada
  • Muhammadiyah University of Surakarta
  • Universitas Maritim Raja Ali Haji
  • Malikussaleh University
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Agus SihabuddinUniversitas Gadjah Mada2
Harliana HarlianaAffiliation unknown1
Bhakti SusiloAffiliation unknown1
Mutammimul UlaMalikussaleh University1
Harry Ganda NugrahaUniversitas Gadjah Mada1
Izmy Alwiah MusdarUniversitas Gadjah Mada1
Devid Haryalesmana WahidUniversitas Gadjah Mada1
Pradita Eko Prasetyo UtomoUniversitas Gadjah Mada1
Azizah FatmawatiMuhammadiyah University of Surakarta1
Nisa RNAMuhammadiyah University of Surakarta1
Muhammad FahrurroziUniversitas Gadjah Mada1
Ferdi ChahyadiUniversitas Maritim Raja Ali Haji1
Hendra KurniawanUniversitas Maritim Raja Ali Haji1
Sigit PriyantaUniversitas Gadjah Mada1
Winda YulitaUniversitas Gadjah Mada1
Abram Setyo PrabowoUniversitas Gadjah Mada1
Yayang Eluis Bali MawartikaUniversitas Gadjah Mada1
Muh Amin NurrohmatUniversitas Gadjah Mada1
Taufan Bagus Dwi Putra AditamaUniversitas Gadjah Mada1
Fauzan IshlakhuddinUniversitas Gadjah Mada1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation</dc:title>
	<dc:creator>Paskalathis, Victor</dc:creator>
	<dc:creator>SN, Azhari</dc:creator>
	<dc:subject xml:lang="en-US">Ant Colony Optimization; Pickup and Delivery Problem; highest savings; crowdsourced; trip consolidation</dc:subject>
	<dc:description xml:lang="en-US">Common practice in crowdsourced delivery services is through direct delivery. That  is by dispatching direct trip to a driver nearby the origin location. The total distance can be reduced through multiple pickup and delivery by increasing the number of requests in a trip.The research implements exact algorithm to solve the consolidation problem with up to 3 requests in a trip. Greedy heuristic is performed to construct initial route based on highest savings. The result is then optimized using Ant Colony Optimization (ACO). Four scenarios are compared. A direct delivery scenarios and three multiple pickup and delivery scenarios. These include 2-consolidated delivery, 3-consolidated delivery, and 3-consolidated delivery optimized with ACO. Four parameters are used to evaluate using Analytical Hierarchical Process (AHP). These include the number of trips, total distance, total duration, and security concerns.The case study is based on Yogyakarta area for a whole day. The final route optimized with ACO shows 178 requests can be completed in 94 trips. Compared to direct delivery, consolidation can provides savings up to 20% in distance and 14% in duration. The evaluation result using AHP shows that ACO scenario is the best scenario. </dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:contributor xml:lang="en-US"></dc:contributor>
	<dc:date>2017-07-31</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/16631</dc:identifier>
	<dc:identifier>10.22146/ijccs.16631</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 11, No 2 (2017): July; 109-118</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.ugm.ac.id/ijccs/article/view/16631/16664</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2017 IJCCS - Indonesian Journal of Computing and Cybernetics Systems</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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