Publicação
Vehicle routing problem with delivery and pickup
| Resumo: | This project, on Vehicle Routing Problem with Delivery and Pickup (VRPDP) aimed at determining the factors that contribute to the quality of a solution and checking the effect of varying the relative sizes of delivery demands to the size of pickup demands. This work was done with a dataset generated by a random uniform distribution of complete graphs with 15, 20, and 25 nodes, with varying relative sizes of the demands at each node to create four scenarios, Indifferent relative sizes of delivery to pickup, Large delivery demand relative to pickup demand, small delivery relative to pickup demand and delivery demand relatively equal to pick up demand at each customer. Three distinct problems were created using these scenarios. A model was created using flow formulation on the GurobiPy solver. The three problems were solved using the model and the result was tabulated. Observations on the table were thoroughly examined and relevant inferences were made on the factors that influence the quality of the VRPDP solution and the effect of varying the relative sizes of the demands. |
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| Autores principais: | Obafemi, Omoniyi Raymondjoy |
| Assunto: | Optimization Routing Logistics planning Transportation optimization Supply chain management Delivery scheduling Pickup scheduling Mixed-integer programming (MIP) |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Aveiro |
| Idioma: | inglês |
| Origem: | RIA - Repositório Institucional da Universidade de Aveiro |
| Resumo: | This project, on Vehicle Routing Problem with Delivery and Pickup (VRPDP) aimed at determining the factors that contribute to the quality of a solution and checking the effect of varying the relative sizes of delivery demands to the size of pickup demands. This work was done with a dataset generated by a random uniform distribution of complete graphs with 15, 20, and 25 nodes, with varying relative sizes of the demands at each node to create four scenarios, Indifferent relative sizes of delivery to pickup, Large delivery demand relative to pickup demand, small delivery relative to pickup demand and delivery demand relatively equal to pick up demand at each customer. Three distinct problems were created using these scenarios. A model was created using flow formulation on the GurobiPy solver. The three problems were solved using the model and the result was tabulated. Observations on the table were thoroughly examined and relevant inferences were made on the factors that influence the quality of the VRPDP solution and the effect of varying the relative sizes of the demands. |
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