Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation
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 ex...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Universitas Gadjah Mada
2017-07-01
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| Series: | IJCCS (Indonesian Journal of Computing and Cybernetics Systems) |
| Subjects: | |
| Online Access: | https://jurnal.ugm.ac.id/ijccs/article/view/16631 |
| _version_ | 1818110437869223936 |
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| author | Victor Paskalathis Azhari SN |
| author_facet | Victor Paskalathis Azhari SN |
| author_sort | Victor Paskalathis |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-11T02:47:08Z |
| format | Article |
| id | doaj.art-34836288983f4d2ba83accf30013a834 |
| institution | Directory Open Access Journal |
| issn | 1978-1520 2460-7258 |
| language | English |
| last_indexed | 2024-12-11T02:47:08Z |
| publishDate | 2017-07-01 |
| publisher | Universitas Gadjah Mada |
| record_format | Article |
| series | IJCCS (Indonesian Journal of Computing and Cybernetics Systems) |
| spelling | doaj.art-34836288983f4d2ba83accf30013a8342022-12-22T01:23:24ZengUniversitas Gadjah MadaIJCCS (Indonesian Journal of Computing and Cybernetics Systems)1978-15202460-72582017-07-0111210911810.22146/ijccs.1663117289Ant Colony Optimization on Crowdsourced Delivery Trip ConsolidationVictor PaskalathisAzhari SNCommon 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.https://jurnal.ugm.ac.id/ijccs/article/view/16631Ant Colony OptimizationPickup and Delivery Problemhighest savingscrowdsourcedtrip consolidation |
| spellingShingle | Victor Paskalathis Azhari SN Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Ant Colony Optimization Pickup and Delivery Problem highest savings crowdsourced trip consolidation |
| title | Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation |
| title_full | Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation |
| title_fullStr | Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation |
| title_full_unstemmed | Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation |
| title_short | Ant Colony Optimization on Crowdsourced Delivery Trip Consolidation |
| title_sort | ant colony optimization on crowdsourced delivery trip consolidation |
| topic | Ant Colony Optimization Pickup and Delivery Problem highest savings crowdsourced trip consolidation |
| url | https://jurnal.ugm.ac.id/ijccs/article/view/16631 |
| work_keys_str_mv | AT victorpaskalathis antcolonyoptimizationoncrowdsourceddeliverytripconsolidation AT azharisn antcolonyoptimizationoncrowdsourceddeliverytripconsolidation |