Examinando por Autor "Jairo R. Montoya-Torres"

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    Green Fuzzy Tourist Trip Design Problem
    (Hindawi, 2022-06-24) Jose Ruiz-Meza; Julio Brito; Jairo R. Montoya-Torres; Ana Castro-Vergara; CORPORACION UNIVERSITARIA DEL CARIBE CECAR; SIMULACIÓN DE TECNOLOGÍAS PARA PROCESOS INDUSTRIALES
    The shift from mass tourism to more personalized travel denotes great importance in the construction of tourist itineraries. Giventhe negative impacts of transport and tourism on the environment, sustainability criteria play an important role. The Tourist TripDesign Problem is related to the design of itineraries for tourists. Planning is complex in tourist regions of developing countrieswhere the information associated with tourist activities is difficult to access, vague, and incomplete. With this information, touristsmust plan their trip, and the conditions and limitations they establish for it are flexible and imprecise. Fuzzy optimization canaddress problems with this type of information and constraints. Therefore, in this paper, an analysis of the tourism supply chain iscarried out, taking as a case study the Department of Sucre on Colombia’s Caribbean coast. A Multiconstraint Multimodal TeamOrienteering Problem with Time Windows and fuzzy constraints is developed to model the tourism trip design problem thatmaximizes profit and minimizes CO2 emissions. The model is tested using datasets from the literature and the real world. Theresults demonstrate consistency with the fuzzy approach and generate a set of low-emission solutions.
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    PublicaciónAcceso abierto
    Location of Urban Logistics Spaces (ULS) for Two-Echelon Distribution Systems
    (AXIOMS, 2021-10) José Ruiz-Meza; Karen Meza-Peralta; Jairo R. Montoya-Torres; JesusGonzalez-Feliu; CORPORACION UNIVERSITARIA DEL CARIBE CECAR; SIMULACIÓN DE TECNOLOGÍAS PARA PROCESOS INDUSTRIALES
    The main concern in city logistics is the need to optimize the movement of goods in urban contexts, and to minimize the multiple costs inherent in logistics operations. Inspired by an application in a medium-sized city in Latin America, this paper develops a bi-objective mixed linear integer programming (MILP) model to locate different types of urban logistics spaces (ULS) for the configuration of a two-echelon urban distribution system. The objective functions seek to minimize the costs associated with distance traveled and relocation, in addition to the costs of violation of time windows. This model considers heterogeneous transport, speed assignment, and time windows. For experimental evaluation, two operational scenarios are considered, and Pareto frontiers are obtained to identify the efficient non-dominated solutions to select the most feasible ones from such a set. A case study of a distribution company of goods for supermarkets in the city of Barranquilla, Colombia, is also used to validate the proposed model. These solutions allow decision-makers to define the configuration of ULS networks for urban product delivery.