Examinando por Autor "Rivera J.C."

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    Ítem
    Heuristic Optimization for the Energy Management and Race Strategy of a Solar Car
    (MDPI AG, 2017-10-01) Betancur E.; Osorio-Gómez G.; Rivera J.C.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)
    Solar cars are known for their energy efficiency, and different races are designed to measure their performance under certain conditions. For these races, in addition to an efficient vehicle, a competition strategy is required to define the optimal speed, with the objective of finishing the race in the shortest possible time using the energy available. Two heuristic optimization methods are implemented to solve this problem, a convergence and performance comparison of both methods is presented. A computational model of the race is developed, including energy input, consumption and storage systems. Based on this model, the different optimization methods are tested on the optimization of the World Solar Challenge 2015 race strategy under two different environmental conditions. A suitable method for solar car racing strategy is developed with the vehicle specifications taken as an independent input to permit the simulation of different solar or electric vehicles.
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    Ítem
    Heuristic Optimization for the Energy Management and Race Strategy of a Solar Car
    (MDPI AG, 2017-10-01) Betancur E.; Osorio-Gómez G.; Rivera J.C.; Betancur E.; Osorio-Gómez G.; Rivera J.C.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y Aplicaciones
    Solar cars are known for their energy efficiency, and different races are designed to measure their performance under certain conditions. For these races, in addition to an efficient vehicle, a competition strategy is required to define the optimal speed, with the objective of finishing the race in the shortest possible time using the energy available. Two heuristic optimization methods are implemented to solve this problem, a convergence and performance comparison of both methods is presented. A computational model of the race is developed, including energy input, consumption and storage systems. Based on this model, the different optimization methods are tested on the optimization of the World Solar Challenge 2015 race strategy under two different environmental conditions. A suitable method for solar car racing strategy is developed with the vehicle specifications taken as an independent input to permit the simulation of different solar or electric vehicles.
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    Ítem
    A Mixed-Integer Linear Programming Model for a Selective Vehicle Routing Problem
    (Springer Verlag, 2018-01-01) Posada A.; Rivera J.C.; Palacio J.D.; Posada A.; Rivera J.C.; Palacio J.D.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y Aplicaciones
    In this paper, we propose a new vehicle routing problem variant. The new problem is a type of selective vehicle routing model in which it is not necessary to visit all nodes, but to visit enough nodes in such a way that all clusters are visited and from which it is possible to cover all nodes. Here, a mixed-integer linear programming formulation (MILP) is proposed in order to model the problem. The MILP is tested by using adapted instances from the generalized vehicle routing problem (GVRP). The model is also tested on small size GVRP instances as a special case of our proposed model. The results allow to evaluate the impact of clusters configuration in solver efficacy. © 2018, Springer Nature Switzerland AG.
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    Ítem
    A Mixed-Integer Linear Programming Model for a Selective Vehicle Routing Problem
    (Springer Verlag, 2018-01-01) Posada A.; Rivera J.C.; Palacio J.D.; Posada A.; Rivera J.C.; Palacio J.D.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    In this paper, we propose a new vehicle routing problem variant. The new problem is a type of selective vehicle routing model in which it is not necessary to visit all nodes, but to visit enough nodes in such a way that all clusters are visited and from which it is possible to cover all nodes. Here, a mixed-integer linear programming formulation (MILP) is proposed in order to model the problem. The MILP is tested by using adapted instances from the generalized vehicle routing problem (GVRP). The model is also tested on small size GVRP instances as a special case of our proposed model. The results allow to evaluate the impact of clusters configuration in solver efficacy. © 2018, Springer Nature Switzerland AG.
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    Ítem
    Mixed-Integer Linear Programming Models for One-Commodity Pickup and Delivery Traveling Salesman Problems
    (Springer Verlag, 2019-01-01) Palacio J.D.; Rivera J.C.; Palacio J.D.; Rivera J.C.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y Aplicaciones
    This article addresses two different pickup and delivery routing problems. In the first one, called the one-commodity pickup and delivery traveling salesman problem, a known amount of a single product is supplied or demanded by a set of two different types of locations (pickup or delivery nodes). Therefore, a capacitated vehicle must visit each location once at a minimum cost. We also deal with the relaxed case where locations can be visited several times. In the last problem, the pickup or delivery operation can be split into several smaller pickups or deliveries, and also locations can be used as temporal storage points with the aim of reducing the cost of the route. To solve these problems, we present two mixed-integer linear programming models and we solve them via commercial solver. We analyze how several visits to a single location may improve solution quality and we also show that our simple strategy has a good performance for instances with up to 60 locations. © 2019, Springer Nature Switzerland AG.
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    Ítem
    Mixed-Integer Linear Programming Models for One-Commodity Pickup and Delivery Traveling Salesman Problems
    (Springer Verlag, 2019-01-01) Palacio J.D.; Rivera J.C.; Palacio J.D.; Rivera J.C.; Universidad EAFIT. Departamento de Ciencias; Modelado Matemático
    This article addresses two different pickup and delivery routing problems. In the first one, called the one-commodity pickup and delivery traveling salesman problem, a known amount of a single product is supplied or demanded by a set of two different types of locations (pickup or delivery nodes). Therefore, a capacitated vehicle must visit each location once at a minimum cost. We also deal with the relaxed case where locations can be visited several times. In the last problem, the pickup or delivery operation can be split into several smaller pickups or deliveries, and also locations can be used as temporal storage points with the aim of reducing the cost of the route. To solve these problems, we present two mixed-integer linear programming models and we solve them via commercial solver. We analyze how several visits to a single location may improve solution quality and we also show that our simple strategy has a good performance for instances with up to 60 locations. © 2019, Springer Nature Switzerland AG.
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    Ítem
    A multi-start evolutionary local search for the one-commodity pickup and delivery traveling salesman problem
    (Springer Netherlands) Palacio J.D.; Rivera J.C.; Universidad EAFIT. Escuela de Ciencias; Modelado Matemático
    This article addresses the one-commodity pickup and delivery traveling salesman problem (1-PDTSP), which is a generalization of the well-known traveling salesman problem. The 1-PDTSP aims to find a Hamiltonian tour in which a set of supply points (pickup locations), demand points (delivery locations) are visited and, the total traveled distance is minimized. We propose a hybrid metaheuristic based on multi-start evolutionary local search and variable neighborhood descent to solve the 1-PDTSP. To test the performance of our algorithm, we solve instances with up to 500 nodes available in the literature and we demonstrate that our approach is able to provide competitive results when comparing to other existing strategies. Since a direct application of the 1-PDTSP arises as the bicycle repositioning problem, we also use our metaheuristic algorithm to solve a set of real-case instances based on EnCicla, the bicycle sharing system in the Aburrá Valley (Antioquia, Colombia). © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
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    Ítem
    A multi-start evolutionary local search for the one-commodity pickup and delivery traveling salesman problem
    (Springer Netherlands) Palacio J.D.; Rivera J.C.; Palacio J.D.; Rivera J.C.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y Aplicaciones
    This article addresses the one-commodity pickup and delivery traveling salesman problem (1-PDTSP), which is a generalization of the well-known traveling salesman problem. The 1-PDTSP aims to find a Hamiltonian tour in which a set of supply points (pickup locations), demand points (delivery locations) are visited and, the total traveled distance is minimized. We propose a hybrid metaheuristic based on multi-start evolutionary local search and variable neighborhood descent to solve the 1-PDTSP. To test the performance of our algorithm, we solve instances with up to 500 nodes available in the literature and we demonstrate that our approach is able to provide competitive results when comparing to other existing strategies. Since a direct application of the 1-PDTSP arises as the bicycle repositioning problem, we also use our metaheuristic algorithm to solve a set of real-case instances based on EnCicla, the bicycle sharing system in the Aburrá Valley (Antioquia, Colombia). © 2020, Springer Science+Business Media, LLC, part of Springer Nature.