Browsing by Author "Vera, Jorge"

Now showing 1 - 8 of 8
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    A robust optimization approach to wine grape harvesting scheduling
    (ELSEVIER, 2010) Bohle, Carlos; Maturana, Sergio; Vera, Jorge
    Optimization models are increasingly being used in agricultural planning. However, the inherent uncertainties present in agriculture make it difficult. In recent years, robust optimization has emerged as a methodology that allows dealing with uncertainty in optimization models, even when probabilistic knowledge of the phenomenon is incomplete. In this paper, we consider a wine grape harvesting scheduling optimization problem subject to several uncertainties, such as the actual productivity that can be achieved when harvesting. We study how effective robust optimization is solving this problem in practice. We develop alternative robust models and show results for some test problems obtained from actual wine industry problems. (C) 2008 Elsevier B.V. All rights reserved.
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    Activation of Intra-nodose Ganglion P2X7 Receptors Elicit Increases in Neuronal Activity
    (2023) Alcayaga, Julio; Vera, Jorge; Reyna-Jeldes, Mauricio; Covarrubias, Alejandra A. A.; Coddou, Claudio; Diaz-Jara, Esteban; Del Rio, Rodrigo; Retamal, Mauricio A. A.
    Vagus nerve innervates several organs including the heart, stomach, and pancreas among others. Somas of sensory neurons that project through the vagal nerve are located in the nodose ganglion. The presence of purinergic receptors has been reported in neurons and satellite glial cells in several sensory ganglia. In the nodose ganglion, calcium depletion-induced increases in neuron activity can be partly reversed by P2X7 blockers applied directly into the ganglion. The later suggest a possible role of P2X7 receptors in the modulation of neuronal activity within this sensory ganglion. We aimed to characterize the response to P2X7 activation in nodose ganglion neurons under physiological conditions. Using an ex vivo preparation for electrophysiological recordings of the neural discharges of nodose ganglion neurons, we found that treatments with ATP induce transient neuronal activity increases. Also, we found a concentration-dependent increase in neural activity in response to Bz-ATP (ED50 = 0.62 mM, a selective P2X7 receptor agonist), with a clear desensitization pattern when applied every similar to 30 s. Electrophysiological recordings from isolated nodose ganglion neurons reveal no differences in the responses to Bz-ATP and ATP. Finally, we showed that the P2X7 receptor was expressed in the rat nodose ganglion, both in neurons and satellite glial cells. Additionally, a P2X7 receptor negative allosteric modulator decreased the duration of Bz-ATP-induced maximal responses without affecting their amplitude. Our results show the presence of functional P2X7 receptors under physiological conditions within the nodose ganglion of the rat, and suggest that ATP modulation of nodose ganglion activity may be in part mediated by the activation of P2X7 receptors.
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    An optimization approach for scheduling wine grape harvest operations
    (ELSEVIER, 2008) Ferrer, Juan Carlos; Mac Cawley, Alejandro; Maturana, Sergio; Toloza, Sergio; Vera, Jorge
    This article presents a practical tool for optimally scheduling wine grape harvesting operations taking into account both operational costs and grape quality. We solve a mixed-integer linear programming model to support harvest scheduling, labor allocation, and routing decisions. A quality loss function is used to represent wine quality reduction at each vineyard block due to premature or deferred harvest with respect to an optimal date. We present computational results which show that the proposed tool could be used to support grape harvest planning in a large vineyard, at both a tactical and operational level, (C) 2007 Elsevier B.V. All rights reserved.
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    Managing the unknown: A distributionally robust model for the admission planning problem under uncertain length of stay
    (2021) Batista, Ana; Pozo, David; Vera, Jorge
    The admission planning problem in the inpatient service aims to provide patient access and to guarantee expected levels of bed utilization. However, uncertainty in the patient's length of stay and bed availability challenge the accomplishment of that objective. This research addresses the off-line admission planning problem with uncertain length of stay. We study the coordinated decisions of scheduling and allocation for the patient-to-room admission problem assuming heterogeneous patient types and time-varying capacity. The objective is to maximize the weighted sum of the patient's admission benefit while reducing the cost of overstay. We present a distributionally robust optimization (DRO) framework that is distribution-free; it considers that known information is limited only to the first moment and the support set of the true probability distribution. The framework is robust against the infinite set of probability distribution functions that could represent the stochastic process of the patient's length of stay. To test the performance of the proposed DRO approach, we compared it with benchmark models employing a real data set from a public hospital in Chile. The results show that our approach outperforms the evaluated models in both reliability and computational efficiency. We provide insights to practitioners and hospital decision-makers to anticipate admission decisions while considering the randomness of the length of stay at the tactical-operational level.
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    Morphological trends in main stem of Pinus radiata D. Don: Transition between vegetative and reproductive phase
    (TAYLOR & FRANCIS AS, 2007) Fernandez, Maria Paulina; Norero, Aldo; Barthelemy, Daniel; Vera, Jorge
    Developmental patterns of structural units of the main tree axis of Pinus radiata were investigated in two plantations in Chile growing under different ecological conditions. Environmental characteristics of sites were recorded and structural features of sample trees were measured. Annual shoot length, number of growth units per annual shoot, growth unit length, and number of branches and cones per growth unit were statistically compared between sites and between vegetative and reproductive phases of trees. No clear pattern of stand development was apparent when variables were directly examined in terms of actual dimensions ( cm) and time scale ( years). In contrast, common patterns of development of structural parameters were indicated after dimensions and time were normalized so as to express them on a ontogenetic scale. The number of growth units per annual shoot and average length of annual shoot increased during the juvenile stage of development. Transition from juvenile to mature stages brought about a change in this trend, either stabilizing or reversing the pattern of development and size of these structural elements. The practical consequence of these changes on wood quality for industrial purposes is discussed.
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    Risk averse retail pricing with robust demand forecasting
    (ELSEVIER SCIENCE BV, 2012) Ferrer, Juan Carlos; Oyarzun, Diego; Vera, Jorge
    Good demand estimates are the key to effective pricing decision-making. However, they are subject to a high degree of uncertainty due to various factors that are unpredictable or difficult to model, thus making pricing decisions risky. This research provides a simple proposal for a robust optimization methodology that incorporates both demand uncertainty and the decision maker's degree of risk aversion. Uncertainty is explicitly considered for two coefficients of a linear demand function, price expressions are derived, and a criterion is proposed for defining the degree of risk aversion. The resulting model is also applied to an exponential demand case to better reflect a more realistic retail setting. (C) 2011 Elsevier B.V. All rights reserved.
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    Robust capabilities design and optimization for a modular block-based organization
    (2024) San Martin, Luis; Vera, Jorge
    Several organizations perform their tasks by combining different groups of people, equipment, etc., in such a way as to reach a goal. These modules, which we call building blocks (BB), have capabilities and their combination provides an overall capability for the whole organization. How to optimally combine those blocks to achieve capabilities for certain goals is what we address in this work. Therefore, we propose a mathematical optimization model in which binary variables represent the allocation of BBs under an additive rule, i.e. all modules linearly contribute with a specific capability which is later aggregated to build the global desired capability balance. An important aspect to consider is the existence of uncertainty, especially in the capabilities. To handle this, we present a reformulation of the optimization model using Robust Optimization, particularly in the cardinality-constrained robust counterpart for the capability balance constraints. Computational results show that the effects of uncertainty can be efficiently controlled by the robust solution at optimality.
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    Scheduling production for a sawmill: A comparison of a mathematical model versus a heuristic
    (PERGAMON-ELSEVIER SCIENCE LTD, 2010) Maturana, Sergio; Pizani, Enzo; Vera, Jorge
    Sawmill production scheduling is complex. It involves determining which logs to process taking into account the diameter, length, and grade of each log, on one hand, and the finished products that are needed to fulfill the orders, on the other. The cutting pattern determines which products are generated and also the yield, which is how much of the volume of the log ends as finished products. We used two approaches to solve the problem: a mathematical model, which calculates the volume and the schedule of various types of logs, and a heuristic that solves the problem by systematically applying the criteria used by a sawmill programmer in southern Chile. We compare the results of using both approaches under various scenarios in a 6 week planning horizon, with the mathematical model showing a superior performance in almost all instances except two, were both found the optimal solution. The proposed mathematical model can be solved in a relatively short time, which makes it a suitable basis of a practical optimization-based decision support system. (C) 2010 Elsevier Ltd. All rights reserved.