16 research outputs found

    Revisión del estado del arte del problema de ruteo abierto (OVRP)

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    En este documento se lleva a cabo una revisión bibliográfica del estado del arte del problema de ruteo abierto (OVRP; Open Vehicle Routing Problem). Se realiza la definición del problema, una clasificación de sus variantes y de los artículos e investigaciones publicadas en las bibliotecas virtuales: Scopus, Science Direct y Google Scholar acerca del tema. Además, se plantean los modelos de solución utilizados por los autores, las aplicaciones del estudio y las tendencias o futuras líneas de investigación. El OVRP es un problema de planificación de rutas de transporte, generalización del Problema del Agente Viajero muy conocido y ampliamente estudiado, tiene como característica diferenciadora que los vehículos una vez finalizadas las entregas correspondientes no están obligados a regresar al punto de partida o depósito. La revisión observa lo publicado hasta mayo del año 2017

    A solution method for a two-layer sustainable supply chain distribution model

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    This article presents an effective solution method for a two-layer, NP-hard sustainable supply chain distribution model. A DoE-guided MOGA-II optimiser based solution method is proposed for locating a set of non-dominated solutions distributed along the Pareto frontier. The solution method allows decision-makers to prioritise the realistic solutions, while focusing on alternate transportation scenarios. The solution method has been implemented for the case of an Irish dairy processing industry׳s two-layer supply chain network. The DoE generates 6100 real feasible solutions after 100 generations of the MOGA-II optimiser which are then refined using statistical experimentation. As the decision-maker is presented with a choice of several distribution routes on the demand side of the two-layer network, TOPSIS is applied to rank the set of non-dominated solutions thus facilitating the selection of the best sustainable distribution route. The solution method characterises the Pareto solutions from disparate scenarios through numerical and statistical experimentations. A set of realistic routes from plants to consumers is derived and mapped which minimises total CO2 emissions and costs where it can be seen that the solution method outperforms existing solution methods

    Routing Applications in Newspaper Delivery

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    -The goal of this report is to give an up-to-date account of routing applications in the newspaper business. We describe the newspaper supply chain, and focus on the “last mile” distribution that has been advocated as an application of arc routing in the literature. A literature survey is provided, followed by a discussion of the arc routing model and its adequacy to newspaper applications. A more general and normally more adequate model: The Node, Edge, and Arc Routing Problem, is discussed. Characteristics of routing problems in carrier delivery are presented, together with a case study from the development of a web-based route design and revision system. Finally, summary, conclusions, and prospects for the future are given

    An evaluation of three DoE-guided meta-heuristic-based solution methods for a three-echelon sustainable distribution network

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    This article evaluates the efficiency of three meta-heuristic optimiser (viz. MOGA-II, MOPSO and NSGA-II)-based solution methods for designing a sustainable three-echelon distribution network. The distribution network employs a bi-objective location-routing model. Due to the mathematically NP-hard nature of the model a multi-disciplinary optimisation commercial platform, modeFRONTIER®, is adopted to utilise the solution methods. The proposed Design of Experiment (DoE)-guided solution methods are of two phased that solve the NP-hard model to attain minimal total costs and total CO2 emission from transportation. Convergence of the optimisers are tested and compared. Ranking of the realistic results are examined using Pareto frontiers and the Technique for Order Preference by Similarity to Ideal Solution approach, followed by determination of the optimal transportation routes. A case of an Irish dairy processing industry’s three-echelon logistics network is considered to validate the solution methods. The results obtained through the proposed methods provide information on open/closed distribution centres (DCs), vehicle routing patterns connecting plants to DCs, open DCs to retailers and retailers to retailers, and number of trucks required in each route to transport the products. It is found that the DoE-guided NSGA-II optimiser based solution is more efficient when compared with the DoE-guided MOGA-II and MOPSO optimiser based solution methods in solving the bi-objective NP-hard three-echelon sustainable model. This efficient solution method enable managers to structure the physical distribution network on the demand side of a logistics network, minimising total cost and total CO2 emission from transportation while satisfying all operational constraints

    Tabu Search: A Comparative Study

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    Proposta de um modelo de roteamento aberto de veículos em uma instituição prestadora de serviços de saúde

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    This research article presents an optimization model based on the application of two heuristics for a real situation of routing a fleet of vehicles of an Institution Provider of Health Services (IPS) to transport their patients. A quantitative study was carried out by applying the heuristics of the nearest neighbor and that of the modified nearest neighbor as this type of routing is of the COVRP type, for its initials in English: capacitated open vehicle routing problem. The cost table, the distance matrix construction algorithm and the heuristic algorithms are presented. The results indicate that the nearest neighbor heuristic offers a solution with a lower cost than that of the modified nearest neighbor since the savings would be 7.34% and 6.05% with respect to the current cost.En este artículo de investigación se  presenta un modelo de optimización basado en la aplicación de dos heurísticas para una situación real de enrutamiento de una flota de vehículos de una Institución Prestadora de Servicios de Salud (IPS) para transportar sus pacientes. Se realizó un estudio cuantitativo mediante la aplicación de las heurísticas del vecino más cercano y la del vecino más cercano modificada ya que este tipo de enrutamiento es del tipo COVRP, por sus siglas en inglés: capacited opened vehicle routing problem. Se presenta la tabla de desglose de los costos, el algoritmo de construcción de la matriz de distancias y los algoritmos para las heurísticas. Los resultados indican que la heurística del vecino más cercano ofrece una solución con un costo menor que la del vecino más cercano modificada ya que los ahorros serían del 7,34% y 6,05% respecto al costo actual.Este artigo de pesquisa apresenta um modelo de otimização baseado na aplicação de duas heurísticas para uma real situação de roteamento de uma frota de veículos de uma Instituição de Prestadores de Serviços de Saúde (IPS) para o transporte de seus pacientes. Um estudo quantitativo foi realizado aplicando as heurísticas do vizinho mais próximo e do vizinho vizinho modificado, uma vez que esse tipo de roteamento é do tipo COVRP, por sua sigla em inglês: capacited open vehicle routing problem. A tabela de decomposição de custos, o algoritmo para a construção da matriz de distância e os algoritmos para as heurísticas são apresentados. Os resultados indicam que a heurística do vizinho mais próximo oferece uma solução com custo menor que o vizinho mais próximo modificado, uma vez que a economia seria de 7,34% e 6,05% em relação ao custo atual

    Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows

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    The vehicle routing problem with time windows (VRPTW) is a non-deterministictime hard (NP-hard) with combinatorial optimization problem (COP). The Artificial Bee Colony (ABC) is a popular swarm intelligence algorithm for COP. In this study, existing Modified ABC (MABC) algorithm is revised to solve the VRPTW. While MABC has been reported to be successful, it does have some drawbacks, including a lack of neighbourhood structure selection during the intensification process, a lack of knowledge in population initialization, and occasional stops proceeding the global optimum. This study proposes an enhanced Modified ABC (E-MABC) algorithm which includes (i) N-MABC that overcomes the shortage of neighborhood selection by exchanging the neighborhood structure between two different routes in the solution; (ii) MABC-ACS that solves the issues of knowledge absence in MABC population initialization by incorporating ant colony system heuristics, and (iii) PMABC which addresses the occasional stops proceeding to the global optimum by introducing perturbation that accepts an abandoned solution and jumps out of a local optimum. The proposed algorithm was evaluated using benchmark datasets comprising 56 VRPTW instances and 56 Pickup and Delivery Problems with Time Windows (PDPTW). The performance has been measured using the travelled distance (TD) and the number of deployed vehicles (NV). The results showed that the proposed E-MABC has lower TD and NV than the benchmarked MABC and other algorithms. The E-MABC algorithm is better than the MABC by 96.62%, MOLNS by 87.5%, GAPSO by 53.57%, MODLEM by 76.78%, and RRGA by 42.85% in terms of TD. Additionally, the E-MABC algorithm is better than the MABC by 42.85%, MOLNS by 17.85%, GA-PSO and RRGA by 28.57%, and MODLEN by 46.42% in terms of NV. This indicates that the proposed E-MABC algorithm is promising and effective for the VRPTW and PDPTW, and thus can compete in other routing problems and COPs
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