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An ant colony optimisation approach to scheduling truck and drone delivery systems
Thesis (PhD)--Stellenbosch University, 2022
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| Format: | Thesis |
| Language: | en_ZA |
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Stellenbosch : Stellenbosch University
2022
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| _version_ | 1867613931619483648 |
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| access_status_str | Open Access |
| author | Tsietsi John, Moremi. |
| author2 | Grobler, Jacomine |
| author_browse | Grobler, Jacomine Tsietsi John, Moremi. |
| author_facet | Grobler, Jacomine Tsietsi John, Moremi. |
| author_sort | Tsietsi John, Moremi. |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (PhD)--Stellenbosch University, 2022 |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/124509 |
| institution | Stellenbosch University (South Africa) |
| language | en_ZA |
| last_indexed | 2026-06-10T12:43:59.464Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/124509 An ant colony optimisation approach to scheduling truck and drone delivery systems Tsietsi John, Moremi. Grobler, Jacomine Kaminsky, Philip. Ant algorithms Ant colony -- Optimization Vehicle Routing Problem and Drones (VRPD) Vehicle Routing Problem and Drones Time Window (VRPDTW) Mathematical optimization Transportation -- Planning Delivery systems – Optimization Business logistics Thesis (PhD)--Stellenbosch University, 2022 ENGLISH SUMMARY: ‘Last mile’ logistic scheduling is a complex problem businesses are facing today. Competitive pressure has increased with technological growth. The speed of delivering parcels to customers can be an excellent source of competitive advantage, since businesses are facing the challenge of efficiently delivering parcels to customers on a daily basis. The use of delivery drones in conjunction with traditional delivery vehicles is a new highly promising research direction explored in this thesis. This dissertation proposes various truck and drone delivery system optimisation problems where a delivery drone is launched from a purpose-built truck, completes additional deliveries while the truck is en route between two customer locations, and intercepts the truck after completing the additional delivery. The dissertation describes the development of an ant colony optimisation algorithm used to solve the problem. More specifically, an ant colony system with k-means clustering was used in this research. Adaptive algorithm control parameters were also used to ensure an acceptable balance between exploration and exploitation throughout the search process. The algorithm was tested on drone scheduling benchmark problems, optimal solution and other population-based metaheuristics and compared against a truck only delivery system. It was shown that the truck and drone delivery system has a significant positive impact on delivery time performance. AFRIKAANS OPSOMMING: ‘Last mile’ skedulering is ’n ingewikkelde probleem wat ondernemings vandag moet kan anteer. Mededingende druk het toegeneem met tegnologiese groei. Die spoed van die aflewering van pakkies aan kliënte kan ’n uitstekende bron van mededingende voordeel wees, aangesien ondernemings daagliks die uitdaging ondervind om pakkies doeltreffend aan kliënte te lewer. Die gebruik van onbemande lugvoertuie saam met tradisionele afleweringsvoertuie is ’n nuwe, baie belowende navorsingsrigting wat in hierdie tesis ondersoek word. Hierdie verhandeling beskryf ’n vragmotor-lugvoertuig afleweringstelsel waar ’n onbemande lugvoertuig vanaf ’n doelgemaakte vragmotor gelanseer word, addisionele aflewerings voltooi terwyl die vragmotor tussen twee kliënte beweeg, en die vragmotor onderskep nadat die addisionele aflewering voltooi is. Die verhandeling beskryf die ontwikkeling van ’n mierkolonieoptimeringsalgoritme wat gebruik word om die probleem op te los. Meer spesifiek, is ’n mierkoloniestelsel in hierdie navorsing gebruik. Aanpasbare algoritme beheerparameters is ook gebruik om ’n aanvaarbare balans tussen eksplorasie en ontginning gedurende die soekproses te verseker. Die algoritme is getoets op standaard probleme vir aflewerings lugvoertuig skedulering en vergelyk met ’n afleweringstelsel wat slegs uit tradisionele voertuie bestaan. Daar word gewys dat die vragmotor-lugvoertuig afleweringstelsel ’n beduidende positiewe invloed op die afleweringstydprestasie het. Doctoral 2022-01-31T14:45:53Z 2022-04-29T09:17:03Z 2022-01-31T14:45:53Z 2022-04-29T09:17:03Z 2022-04 Thesis http://hdl.handle.net/10019.1/124509 en_ZA Stellenbosch University xxi, 199 pages : illustrations application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Ant algorithms Ant colony -- Optimization Vehicle Routing Problem and Drones (VRPD) Vehicle Routing Problem and Drones Time Window (VRPDTW) Mathematical optimization Transportation -- Planning Delivery systems – Optimization Business logistics Tsietsi John, Moremi. An ant colony optimisation approach to scheduling truck and drone delivery systems |
| title | An ant colony optimisation approach to scheduling truck and drone delivery systems |
| title_full | An ant colony optimisation approach to scheduling truck and drone delivery systems |
| title_fullStr | An ant colony optimisation approach to scheduling truck and drone delivery systems |
| title_full_unstemmed | An ant colony optimisation approach to scheduling truck and drone delivery systems |
| title_short | An ant colony optimisation approach to scheduling truck and drone delivery systems |
| title_sort | ant colony optimisation approach to scheduling truck and drone delivery systems |
| topic | Ant algorithms Ant colony -- Optimization Vehicle Routing Problem and Drones (VRPD) Vehicle Routing Problem and Drones Time Window (VRPDTW) Mathematical optimization Transportation -- Planning Delivery systems – Optimization Business logistics |
| url | http://hdl.handle.net/10019.1/124509 |
| work_keys_str_mv | AT tsietsijohnmoremi anantcolonyoptimisationapproachtoschedulingtruckanddronedeliverysystems AT tsietsijohnmoremi antcolonyoptimisationapproachtoschedulingtruckanddronedeliverysystems |