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    Optimization of Water and Land Allocation in Fruit Orchards over a 20-Year Period
    (MDPI AG, 2024-12-24)
    Luciano Quezada
    ;
    Eduardo Holzapfel
    ;
    Mathias Kuschel-Otárola
    ;
    Mario Lillo-Saavedra
    ;
    RIVERA SALAZAR, DIEGO ANDRÉS  
    <jats:p>This study proposes a nonlinear programming model for the optimization of water and land allocation in a 1000 ha orchard over a 20-year period to maximize farmers’ net profits. Different scenarios were evaluated, including equitable and unrestricted land allocation, and the risks associated with fruit production were considered. Additionally, a sensitivity analysis that focused on the variability of labor and water availability was conducted. The results reveal that with equitable land allocations and no constraints on the cultivated area, cherry emerges as the most profitable crop, although there are large risks associated with its price volatility. The introduction of risk and land allocation constraints highlights the importance of crop diversification in mitigating economic risks. A sensitivity analysis indicated that reductions in water and labor availability significantly affect the optimal cropping pattern of an orchard, suggesting that the efficient and adaptive management of resources is required. The proposed optimal cropping pattern maintains the economic viability of the orchard even with 70% and 24% reductions in water and labor, respectively. This approach underscores the importance of implementing resilient and sustainable agricultural strategies to ensure food security and increase economic stability in the face of changing climatic and labor conditions.</jats:p>
      2Scopus© Citations 6
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    A Road Pricing Model for Congested Highways Based on Link Densities
    (2017)
    Louis de Grange
    ;
    TRONCOSO OLCHEVSKAIA, RODRIGO VLADISLAV  
    ;
    Felipe González  
    <jats:p>A road pricing model is presented that determines tolls for congested highways. The main contribution of this paper is to include density explicitly in the pricing scheme and not just flow and time. The methodology solves a nonlinear constrained optimization problem whose objective function maximizes toll revenue or highway use (2 scenarios). The results show that the optimal tolls depend on highway design and the level of congestion. The model parameters are estimated from a Chile’s highway data. Significant differences were found between the highway’s observed tolls and the optimal toll levels for the two scenarios. The proposed approach could be applied to either planned highway concessions with recovery of capital costs or the extension or retendering of existing concessions.</jats:p>
      2Scopus© Citations 6
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    Measuring efficiency in the Chilean wine industry: a robust DEA approach
    (2020)
    VARAS VALDÉS, MAURICIO ANDRÉS  
    ;
    Franco Basso
    ;
    Sergio Maturana
    ;
    Raúl Pezoa
    ;
    Marcelo Weyler
    Scopus© Citations 15  2
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    An integrated multi-criteria decision analysis and optimization modeling approach to spatially operational road repair decisions
    (2021)
    Sättar Ezzati
    ;
    PALMA INFANTE, CRISTIAN DERECK  
    ;
    Pete Bettinger
    ;
    Ljusk Ola Eriksson
    ;
    Anjali Awasthi
    In this study, we developed a generic cost-effective approach for spatially explicit decision support involving the allocation of road repair treatments. The approach begins with an assessment of the existing road condition to identify the extent of environmental impacts and to determine road repair regimes in a subjective manner using group-decision making efforts. An integer programming model is then formulated by combining expert opinions with operational costs to guide repair schedules required for each road segment at the operational planning level. To demonstrate model performance, we applied it to a 400 km<jats:sup>2</jats:sup> landscape consisting of 289 km of paved roads in the mountainous region of the Hyrcanian forests in Iran. We assessed sensitivity of the inputs, such as weight verification, budgetary limitations, and rehabilitation weights. The results of the subjective analysis show that 76% of the roads analyzed in these forests must be prioritized to receive treatments as intended for logistical purposes. Incorporating the extent of environmental dimensions into operational costs allows us to generate an optimal tradeoff curve by selecting an appropriate treatment for segments of a road network. The approach demonstrated here can be used to design detailed alternative solutions for addressing spatially-informed road decisions under various terrain conditions.
      4Scopus© Citations 5
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      1Scopus© Citations 8
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      12Scopus© Citations 52
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    A maximum entropy optimization model for origin-destination trip matrix estimation with fuzzy entropic parameters
    (2021)
    Héctor López-Ospina
    ;
    Cristián E. Cortés
    ;
    PÉREZ, JUAN
    ;
    Romario Peña
    ;
    Juan Carlos Figueroa-García
      16Scopus© Citations 13