Drones-Vehicle Routing Problems / Abderraouf Hamata

Public ISBD Titre : Drones-Vehicle Routing Problems Type de document : document électronique Auteurs : Abderraouf Hamata, Auteur ; Alaa eddin Abdelmalek, Auteur ; Abd elouahab Abdelmalek, Auteur ; I Bouras, Directeur de thèse Editeur : Sétif:UFA1 Année de publication : 2024 Importance : 1 vol (57 f .) Format : 29 cm Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : VRP K-means Clustering Integerprogramming Index. décimale : 004 Informatique Résumé : ThisworkaddressestheVehicleRoutingProblemwithDrones(VRP-D),acomplexlogistics challenge that involves coordinating a truck and multiple delivery drones tominimize total delivery time. In this hybrid system, a truck carries the drones and goods,acting as a mobile base from which the drones are deployed to serve customers withintheir operational range. The aim is to optimize the truck’s route and the drones’ deliveryschedules,takingintoaccountbothgroundandaerialconstraints. To solve the problem, we used a two-phase algorithm: first, customer locations areclustered using the K-Means algorithm, then, a vehicle routing problem is solved for thedrones within each cluster.This approach optimizes both the truck’s route and the drones’deliveries. Results show significant reductions in total computational time compared tosolvingtheproblemwithoutclustering. Note de contenu : Sommaire Abstract i Tableofcontents ii Listoftables v Introduction 1 1.TheVehicleRoutingProblem: 3 1.1. Introduction: .................................. 3 1.2.Problemdefinition ............................... 4 1.3.Mathemathicalformulations:.......................... 4 1.4.Complixity:................................... 7 1.5. TypesofVRP: ................................. 9 1.5.1. ClassicVRP(VRP):.......................... 9 1.5.2. TheRichVehicleRoutingProblems(RVRP): .. . . . . . . . . . . 10 1.5.3. VRPwithtimewindows(VRPTW): .. . . . . . . . . . . . . . . . 11 1.5.4. Multi-DepotVRP(MDVRP):..................... 11 1.5.5.ThePickupandDeliveryVehicleRoutingProblem(PDVRP):... 12 1.6.Algorithms:................................... 13 1.6.1. Exactalgorithms:............................ 13 1.6.2. Heuristicmethods:........................... 15 2.VehiculRoutingProblemwithDrones 17 2.1.Inroduction:................................... 17 2.2.Definitionofdrones............................... 18 2.2.1. Droneconstruction:........................... 18 2.2.2. Classificationofdrones: .. . . . . . . . . . . . . . . . . . . . . . . 20 2.3. VRPwithDrones: ............................... 20 2.4.Challenges.................................... 22 2.5.Problemformulation.............................. 23 2.5.1.Thecostintheflightsegment:..................... 23 2.5.2. Thecostintheglobalroutes: 25 2.5.3. GlobalProblemFormulation: 26 2.6. Algorithm: 26 3. Two-phasealgorithmtosolvetheVRPwithdrones 35 3.1. Introduction 35 3.2. Problemdescription 36 3.3. Solutiontechnique 36 3.3.1. Phase1:ClusteringUsingK-MeansAlgorithm 36 3.3.2. Phase2:SolvingaVRP-DWithinEachCluster 37 3.4. ApplicationoftheTwo-PhaseAlgorithmonaSmallInstance 43 3.5. Numericalexperiments 45 3.5.1. Datageneration 46 3.5.2. Implementation 46 3.5.3. Results 47 Côte titre : MAI/0949 Drones-Vehicle Routing Problems [document électronique] / Abderraouf Hamata, Auteur ; Alaa eddin Abdelmalek, Auteur ; Abd elouahab Abdelmalek, Auteur ; I Bouras, Directeur de thèse . - [S.l.] : Sétif:UFA1, 2024 . - 1 vol (57 f .) ; 29 cm. Langues : Anglais (eng) Catégories : Thèses & Mémoires:Informatique Mots-clés : VRP K-means Clustering Integerprogramming Index. décimale : 004 Informatique Résumé : ThisworkaddressestheVehicleRoutingProblemwithDrones(VRP-D),acomplexlogistics challenge that involves coordinating a truck and multiple delivery drones tominimize total delivery time. In this hybrid system, a truck carries the drones and goods,acting as a mobile base from which the drones are deployed to serve customers withintheir operational range. The aim is to optimize the truck’s route and the drones’ deliveryschedules,takingintoaccountbothgroundandaerialconstraints. To solve the problem, we used a two-phase algorithm: first, customer locations areclustered using the K-Means algorithm, then, a vehicle routing problem is solved for thedrones within each cluster.This approach optimizes both the truck’s route and the drones’deliveries. Results show significant reductions in total computational time compared tosolvingtheproblemwithoutclustering. Note de contenu : Sommaire Abstract i Tableofcontents ii Listoftables v Introduction 1 1.TheVehicleRoutingProblem: 3 1.1. Introduction: .................................. 3 1.2.Problemdefinition ............................... 4 1.3.Mathemathicalformulations:.......................... 4 1.4.Complixity:................................... 7 1.5. TypesofVRP: ................................. 9 1.5.1. ClassicVRP(VRP):.......................... 9 1.5.2. TheRichVehicleRoutingProblems(RVRP): .. . . . . . . . . . . 10 1.5.3. VRPwithtimewindows(VRPTW): .. . . . . . . . . . . . . . . . 11 1.5.4. Multi-DepotVRP(MDVRP):..................... 11 1.5.5.ThePickupandDeliveryVehicleRoutingProblem(PDVRP):... 12 1.6.Algorithms:................................... 13 1.6.1. Exactalgorithms:............................ 13 1.6.2. Heuristicmethods:........................... 15 2.VehiculRoutingProblemwithDrones 17 2.1.Inroduction:................................... 17 2.2.Definitionofdrones............................... 18 2.2.1. Droneconstruction:........................... 18 2.2.2. Classificationofdrones: .. . . . . . . . . . . . . . . . . . . . . . . 20 2.3. VRPwithDrones: ............................... 20 2.4.Challenges.................................... 22 2.5.Problemformulation.............................. 23 2.5.1.Thecostintheflightsegment:..................... 23 2.5.2. Thecostintheglobalroutes: 25 2.5.3. GlobalProblemFormulation: 26 2.6. Algorithm: 26 3. Two-phasealgorithmtosolvetheVRPwithdrones 35 3.1. Introduction 35 3.2. Problemdescription 36 3.3. Solutiontechnique 36 3.3.1. Phase1:ClusteringUsingK-MeansAlgorithm 36 3.3.2. Phase2:SolvingaVRP-DWithinEachCluster 37 3.4. ApplicationoftheTwo-PhaseAlgorithmonaSmallInstance 43 3.5. Numericalexperiments 45 3.5.1. Datageneration 46 3.5.2. Implementation 46 3.5.3. Results 47 Côte titre : MAI/0949

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