Facultad Regional Santa Fe

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    A mathematical modeling for simultaneous routing and scheduling of logging trucks in the forest supply chain
    (Forest Policy and Economics, 2022-01-12) Melchiori, Luciana; Nasini, Graciela; Montagna, Jorge Marcelo; Corsano, Gabriela
    Transportation cost in the forest industry highly impacts on the overall costs of the supply chain, and therefore it must be optimized for improving profitability. Considering the problem characteristics, the decisions related to the transport problem, such as allocation, routing, and scheduling, are usually decoupled, resorting to different decomposition strategies. As a result, suboptimal and underperforming solutions are obtained. In this article, decisions about raw material allocation, routing and scheduling are simultaneously solved through a mixed integer linear programming model. The proposed model involves an arc-based formulation for routing and a time grid discretization, including the definition of loading and unloading shifts for scheduling. This leads to detailed transportation planning for a homogeneous logging truck fleet that must fulfill the demand of varied raw material at minimum cost. Examples and performance tests are provided to assess the capabilities of the proposed exact approach.
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    Resources synchronization in a full truckload pickup and delivery problem : an exact approach
    (Computers and Operations Research, 2022-12-05) Melchiori , Luciana; Nasini, Graciela; Montagna, Jorge Marcelo; Corsano, Gabriela
    In this work, the Unpaired Full Truckload Pickup and Delivery Problem with Resource Synchronization is modeled and solved, where routes must be determined to transport commodities from pickup to delivery locations by a set of vehicles, subject to timing and resource synchronization constraints, to satisfy demands at minimum cost. Unlike previous works, the use of multiple resources for loading and unloading tasks at each location are considered and appropriately managed through a representation using discrete shifts. An integer linear programming model is proposed to simultaneously solve allocation, routing and resources synchronization optimization problems. In order to improve the model performance for large size instances, diverse reformulations, including additional inequalities and symmetric-breaking constraints, are implemented and tested. Moreover, a heuristic procedure is proposed to provide good initial feasible solutions. The capabilities of the proposed approach are assessed through several examples
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    Metodología matemática-algorítmica de Programación de Operaciones aplicada a un caso de estudio de escala industrial
    (2020-12-03) Zuffiaurre, Santiago; Marchetti, Pablo A.
    En este trabajo se presenta una metodología para la programación de operaciones de procesos “batch” en instalaciones multiproducto multietapa. El modelo matemático empleado es de tipo mixto-entero lineal (MILP) y utiliza una representación de ranuras de tiempo (“time slots”). El modelo se complementa con un algoritmo iterativo, basado en la resolución de una secuencia de subproblemas, que permite identificar y fijar la programación de la etapa cuello de botella en cada paso. La metodología propuesta apunta a obtener soluciones de buena calidad para problemas de escala industrial en tiempos de cómputo razonables. Fue aplicada a un caso de estudio real de la industria farmacéutica, que involucra la programación de 30 productos en una planta de 6 etapas y 17 equipos. Si bien no garantiza la optimalidad de la solución hallada, a diferencia de otros aportes de tipo heurístico provee una cota inferior rigurosa que permite medir la calidad de la solución.
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    Efficient scheduling of a real case study of the pharmaceutical industry using a mathematical-algorithmic decomposition methodology
    (ICPR-Americas 2020, 2021-05-12) Stürtz, Josías A.; Marchetti, Pablo A.
    This work presents a mathematical-algorithmic methodology to handle scheduling decisions on multiproduct multistage batch facilities, developed with the aim to solve problems of industrial size. The proposal is based on the iterative construction of a solution by solving a sequence of subproblems associated to each stage, identifying and fixing the critical decisions at each step, and keeping rigorous information on the bounds. The methodology is applied to a real case study obtaining good quality solutions in competitive computing times.