Estudio y desarrollo de un modelo matemático para el problema de rutas escolares (SBRP)

Este trabajo se expone en tres capítulos. En el primero, se muestran las definiciones y ejemplos más importantes para nuestro trabajo, además del estudio de herramientas básicas para la construcción de continuos, como lo son la intersección anidada de continuos, el producto numerable de continuos, el límite inverso de una sucesión inversa de continuos, y una breve exposición sobre la descomposición de continuos.

• Autores: Bustos Gutierrez, Maribel; Pinilla Cifuentes, Astrid Carolina
• Tipo de recurso: http://purl.org/coar/version/c_b1a7d7d4d402bcce
• Fecha de publicación: 2016
• Institución: Universidad Industrial de Santander
• Repositorio: Repositorio UIS
• Idioma: spa
• OAI Identifier: oai:noesis.uis.edu.co:20.500.14071/34780
• Acceso en línea: https://noesis.uis.edu.co/handle/20.500.14071/34780; https://noesis.uis.edu.co
• Palabra clave: Problema De Rutas Escolares (Sbrp); Selección De Paradas; Problema De Ruteo De Vehículos (Vrp); Ramificación Y Acotamiento; Metaheurística; Búsqueda Tabú.; School bus routing problem (SBRP); consists in finding one or more routes on a network of bus stops; with known origin and common destiny; where every student must be assigned to one of these; later each bus to visit those stops according to the route drawn on the network and transfer the students to school. The objective of this research is to solve the problem of school routes using a model of binary integer linear programming; in which seeks to minimize the subset of selected stops; to which students are assigned; as long as they comply with the allowed distance to walk to a stop; and then develop a series of routes that minimize the total distance traveled by all buses. The solution SBRP will through exact methods with the algorithm branch and bound; and by methods approximate the development of a system based on metaheuristic Tabu Search algorithm whose initial solution is provided through the algorithm savings Clarke and Wright. The results obtained by the algorithm; finally were compared with those calculated by the exact method; in order to test the efficiency and effectiveness of the algorithm developed. This comparison showed that; for instances evaluated; the algorithm presented a maximum difference of 10; 5% compared to the optimal solution; but that is offset by a faster computational time 99; 7%.
• License: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)