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Ecological distance-based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve-design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget-constrained optimization problem and conducted a simulation to explore 3 different SCR-informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density-weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space-use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home-range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long-term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density-weighted connectivity or preemptively imposing home-range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high-density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home-range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner. Los modelos de captura-recaptura espacial (CRE) basados en distancias ecológicas son un método prometedor para estimar la densidad animal y la conectividad, las cuales afectan los procesos poblacionales espaciales y, en última instancia, la persistencia de las especies. Exploramos cómo se puede integrar a los modelos CRE en los marcos de diseño de reserva que explícitamente reconocen tanto la distribución espacial de los individuos como su uso del espacio resultante de la estructura del paisaje. Formulamos el diseño de reservas de vida silvestre como un problema de optimización de presupuesto limitado y realizamos una simulación para explorar 3 diferentes objetivos de optimización informados por CRE que priorizaron diferentes metas de conservación mediante la maximización del número de individuos protegidos; la conectividad de la reserva y la conectividad ponderada por la densidad. También estudiamos el efecto sobre nuestros objetivos de hacer que los requerimientos individuales de uso de espacio fuesen satisfechos por la reserva de manera que se pudiese considerar que los individuos estaban protegidos (referidos como restricciones de rango de hogar). La maximización de la densidad de la población local resultó en reservas fragmentadas que probablemente no contribuyan a la persistencia de la población a largo plazo, mientras que la maximización de la conectividad produjo reservas que protegían al menor número de individuos. Sin embargo, la maximización de la conectividad ponderada por la densidad o la imposición preventiva de restricciones de rango de hogar en el diseño de reservas produjo reservas compuestas por conjuntos de parcelas mayormente compactas espacialmente que cubrían áreas de densidad alta en el paisaje con alta conectividad funcional entre ellas. Nuestros resultados cuantifican la extensiónalacualeldiseño de reservas esta limitado por los requerimientos de rango de hogar individuales y resaltan que la consideración del uso de espacio individual en el objetivo y limitaciones puede ayudar al diseño de reservas que equilibren la abundancia y la conectividad de manera biológicamente relevante. 基于生态距离的空间捕获-重捕模型（spatial capture-recapture model, SCR) 有望同时估计动物密度和连 接度，这两者通过影响种群空间过程，最终影响着物种续存。我们探究了如何将 SCR 模型整合到保护区设计框 架中，以兼顾个体的空间分布和对景观结构的空间利用。我们认为野生动物保护区设计可以看作是受预算限制 的最优化问题，并且模拟了三种基于 SCR 信息实现保护目标最优化的情况，即优先考虑保护个体数目最大化、 保护区连接度最优化以及密度加权的连接度最优化。我们还分析了在保护区满足个体:空间利用需求的前提下这 三个目标受到的影响，这个条件是为了确保个体凌到有效保护（即家域约束）。实现局部种群密度最大化会导致 保护区破碎化，这可能不利于种群的长期续存;而考虑连接度最优化则会导致保护区覆盖的个体数最少。然而， 考虑密度加权的连接度最优化，或在保护区设计中优先加人家域约束，则保护区会含有大量空间上紧密的斑块 以覆盖景观中种群密度高的地区，斑块之间功能连接度也较高。本研究结果量化分析了个体的家域需求的限制 对保护区设计的影响程度，并强调了在保护区设计的目标和限制中考虑个体:空间利用将有助于设计出生物学意 义上平衡丰度和连接度的保护区。

Objective: Due to the alarming rise in COVID-19 cases every day in India, numerous academics are already developing a variety of math-based estimation models to forecast the pandemic future course. This paper makes use of publicly available data to anticipate certain COVID-19 trajectories in India. Methods: We used the Auto-Regressive Integrated Moving Average Model, a time series model, to anticipate the number of COVID-19 infected cases every day soon. People need to consume nutritious food that is well-balanced and contains the right number of calories, nutrients, as well as vitamins for strong development, bearing in mind that sustaining and repairing bodily tissues is the goal while preventing unfavorable illnesses and disease. Results: Recent studies have shown that healthy eating can help lower the possibilities of developing cancer, cardiovascular disease and for COVID patients. Therefore, an optimization strategy and LINDO software was used to solve the model. This study offers an exhaustive daily meal plan created especially for hospital patients, acting as a helpful resource for school administrators. With six different food choices, the diet plan makes sure that you get all the nutrients you need each day at a reasonable price. Conclusions: The model is solved using LINDO software in the study, which shows how effective it is when compared to other heuristic techniques like biological algorithms. It is determined through thorough investigation that the chosen meals are both financially and nutritionally feasible to serve in ho spital settings. Hospital patients make up the study’s participants, and each day’s total cost comes to Rs109.34. This cost makes it possible to deliver meals that are minimally more costly but of higher quality, improving the patients’ overall nutritional value. Objetivo: Debido al alarmante aumento de casos de COVID-19 cada día en la India, numerosos académicos ya están desarrollando una variedad de modelos de estimación basados en matemáticas para pronosticar el curso futuro de la pandemia. Este documento utiliza datos disponibles públicamente para anticipar ciertas trayectorias de COVID-19 en la India. Métodos: Utilizamos el modelo de media móvil integrada autorregresiva, un modelo de series temporales, para anticipar el número de casos de infección por COVID-19 todos los días en el corto plazo. Las personas necesitan consumir alimentos nutritivos, bien equilibrados y que contengan la cantidad adecuada de calorías, nutrientes y vitaminas para un desarrollo fuerte, teniendo en cuenta que el objetivo es mantener y reparar los tejidos corporales y, al mismo tiempo, prevenir enfermedades y dolencias desfavorables. Resultados: Estudios recientes han demostrado que una alimentación saludable puede ayudar a reducir las posibilidades de desarrollar cáncer, enfermedades cardiovasculares y en pacientes con COVID. Por lo tanto, se utilizó una estrategia de optimización y el software LINDO para resolver el modelo. Este estudio ofrece un plan de alimentación diario exhaustivo creado especialmente para pacientes hospitalarios, que actúa como un recurso útil para los administradores escolares. Con seis opciones de alimentos diferentes, el plan de dieta garantiza que obtenga todos los nutrientes que necesita cada día a un precio razonable. Conclusiones: El modelo se resuelve utilizando el software LINDO en el estudio, lo que muestra su efectividad en comparación con otras técnicas heurísticas como los algoritmos biológicos. A través de una investigación exhaustiva se determina que las comidas elegidas son viables desde el punto de vista financiero y nutricional para servir en entornos hospitalarios. Los pacientes del hospital constituyen los participantes del estudio y el costo total de cada día asciende a 109,34 rupias. Este costo permite entregar comidas mínimamente más costosas pero de mayor calidad, mejorando el valor nutricional general de los pacientes. Objectivo: Devido ao aumento alarmante de casos diários de COVID-19 na Índia, vários académicos já estão a desenvolver uma variedade de modelos de estimativa baseados em matemática para prever o curso futuro da pandemia. Este artigo utiliza dados disponíveis publicamente para antecipar certas trajetórias da COVID-19 na Índia. Métodos: Usamos o modelo de média móvel integrada auto-regressiva, um modelo de série temporal, para antecipar o número de casos infectados por COVID-19 todos os dias em breve. As pessoas precisam consumir alimentos nutritivos, bem balanceados e que contenham a quantidade certa de calorias, nutrientes e vitaminas para um forte desenvolvimento, tendo em mente que o objetivo é sustentar e reparar os tecidos corporais, ao mesmo tempo que se previnem doenças e enfermidades desfavoráveis. Resultados: Estudos recentes demonstraram que uma alimentação saudável pode ajudar a diminuir as possibilidades de desenvolvimento de cancro, doenças cardiovasculares e para pacientes com COVID. Portanto, uma estratégia de otimização e o software LINDO foram utilizados para resolver o modelo. Este estudo oferece um plano alimentar diário exaustivo criado especialmente para pacientes hospitalares, atuando como um recurso útil para administradores escolares. Com seis opções alimentares diferentes, o plano de dieta garante que você obtenha todos os nutrientes necessários todos os dias a um preço razoável. Conclusões: O modelo é resolvido utilizando o software LINDO no estudo, o que mostra sua eficácia quando comparado a outras técnicas heurísticas como algoritmos biológicos. Através de investigação minuciosa é determinado que as refeições escolhidas são financeiramente e nutricionalmente viáveis para serem servidas em ambientes hospitalares. Os pacientes do hospital constituem os participantes do estudo e o custo total de cada dia chega a Rs109,34. Esse custo permite entregar refeições minimamente mais caras, mas de maior qualidade, melhorando o valor nutricional geral dos pacientes.

All public administration contracts must be evaluated in order to improve their performance while respecting the limits established by laws and regulations. The purpose of this article is to apply an approach to improve the performance of a common building maintenance service contract for the Paraná State Court of Justice (PRCJ), which has a total built area of ​​544 283,79 m² in 224 buildings distributed over 161 counties, by optimizing the territorial partitioning of Paraná State. To partition the state into 14 regions, a binary integer linear programming (BILP) mathematical model is applied to the facilities location problem (FLP) in three scenarios. The results show that Scenario 3 (in which the location of the 14 maintenance offices and the configuration of their areas of activity were optimized) is the best in terms of minimizing the distances traveled by maintenance teams. In this scenario, the total distance traveled would be 9 775 km per day (instead of the current 11 150 km), achieving savings of around 12,3% when compared to the current solution. With this solution, in addition to the distance, the direct and indirect costs associated with the displacement of work teams and the time spent on their corresponding trips would be minimized. Furthermore, the users of maintenance services could be served more quickly, resulting in a higher number of services and greater satisfaction for the target audience of the contract.

The Special Economic Zones (SEZs) are delimited geographic areas located within the borders of a country with the objective of impulsing the local economy of a specific region. The SEZs have multiple labor and fiscal benefits that allow them to enhance the economic level of the region through the generation of quality jobs, export growth, government investment, and technology transfer, just to name a few. China and other countries have demonstrated the benefits of SEZs and the economic impact on the local region. The goal of this article proposes a methodology based on Integer Linear Programming to generate SEZs where the population of the region, the distance and travel time between municipalities, the infrastructure of the region, and the Federal Laws imposed by the governments are considered. Experimental results based on real instances of the Isthmus of Tehuantepec, México, validate the method and enable a graphical visualization of the solution.

In this study, we address the current issues that usually manifest during the programming of university courses, classified as University Course Timetabling Problem, which is considered as a NP-hard problem due to the high computational demand that it requires.To solve the problem, a Mixed Integer Linear Programming model is proposed, which serves as a reference when dimensioning the problem and the restrictions that must be considered. Next, a hybrid metaheuristic method is designed based on the HGATS algorithm, Hybrid Genetic Algorithm Tabu Search Approach, developed by [16], which combines the diversification capacity of the Genetic Algorithm with the strategy of intensification of the Tabu Search Algorithm. Finally, the validation of the proposed algorithm is performed using the data from the programming of the classes from the academic periods 2018-1 and 2018-2 for the academic program of Industrial Engineering at the Industrial University of Santander, obtaining interesting solutions in a reasonable computational time, being that the process of organizing the schedule by the coordinator can last from hours to days, depending on your ability.  

Logistics companies are largely encouraged to make greener their operations through an efficient solution with electric vehicles (EVs). However, the driving range is one of the limiting aspects for the introduction of EVs in logistics fleet, due to the low capacity provided by the batteries to perform the routes. In this regards, it is necessary to set up a framework to virtually increase this battery capacity by locating EV charging stations (EVCSs) along the transportation network for the completion of their routes. By the other side, the Distribution Network Operators (DNOs) express the concern associated with the inclusion of new power demands to be attended (installation of EVCSs) in the Distribution Network (DN), without reducing the optimal power supply management for the end-users. Under these circumstances, in this paper the Electric Vehicle Routing Problem with Backhauls and optimal operation of the Distribution Network (EVRPB-DN) is introduced and formulated as a mixed-integer linear programming model, considering the operation of the DN in conditions of maximum power demand. Different candidate points for the EVs charging are considered to recharge the battery at the end of the linehaul route or during the backhaul route. The problem is formulated as a multi-objective approach where the transportation and power distribution networks operation are modeled. The performance and effectiveness of the proposed formulation is tested in VRPB instance datasets and DN test systems from the literature. Pareto fronts for each instance are presented, using the ε-constraint methodology.

En este trabajo se propone un modelo de programación lineal entera para planificar la producción de un conjunto de artículos finales con demanda independiente. El modelo para la planificación maestra de producción (PMP) está diseñado considerando los costes de producción e inventario, así como las restricciones definidas por el mismo proceso productivo en cuanto a instalaciones y tiempos de producción. El objetivo del modelo propuesto es la minimización de los costes implicados; concretamente, el tiempo ocioso y extra de los recursos, así como la consideración de un nivel mínimo de servicio ligado a la demanda diferida. La validación del modelo considera datos pertenecientes a la demanda de cada producto en un horizonte de 12 semanas y compara cinco escenarios en los que se modifican algunos aspectos del sistema y diferentes niveles de servicio. Por último, los resultados obtenidos para cada uno de los escenarios exponen la mejora obtenida por el modelo propuesto respecto al procedimiento actual en la empresa objeto de estudio. || In this work, we propose an integer linear programming model for production scheduling of a group of finished products with independent demand. The model for the master production scheduling (MPS) is designed by considering production and inventory costs, as well as the productive process constraints regarding installations and production times. The aim of the proposed model is the minimization of the costs involved; specifically, undertime and overtime costs of resources, as well as the consideration of a minimum service level related to the deferred demand. The validation of the model considers data belonging to the demand of each product in a 12-week planning horizon and compares five scenarios in which some characteristics of the system and different service levels are modified. Finally, the results obtained for each one of the scenarios expose the improvement obtained by the proposed model with regard to the current procedure in the studied company.

This article introduces a new mixed integer linear programming model that guarantees the optimal solution to the location and sizing problem of distributed photovoltaic generators in an isolated mini-grid. The solar radiation curves of each node in the mini-grids were considered, and the main objective was to minimize electric power losses in the operation of the system. The model is non-linear in nature because some restrictions are not linear. However, this article proposes the use of linearization techniques to obtain a linear model with a global optimal solution, which can be achieved through commercial solvers; CPLEX in this case. The proposed model was tested in an isolated 14-bus mini-grid, based on real data of topology, demand and generation adapted to a balanced operation. This model shows, as a result, the optimal location of photovoltaic generators and their optimal capacity produced by the maximum active power delivered at the maximum solar irradiation time of the region. It is also evident that the hybrid operation between small hydroelectric power plants and photovoltaic generation improves the network voltage profile and the electric power losses without the use power storage systems.

Due to opportunities for economic and social development in the biofuels market, improvement to the supply chain has become a relevant matter. In agro-industrial supply chains, procurement costs are highly relevant. Since sugarcane is a high performance raw material for ethanol production, this paper proposes a Mixed-Integer Linear Programming Model for cost optimization for harvesting, loading and transportation operations. The model determines the quantity of machines and workers to meet the biofuel plant requirements. Costs of resources for harvesting and loading as well as transportation costs from the land parcel to the production plant are minimized. Also, the model calculates the cost of penalties for shortages (unmet demand) and the cost of equipment idle time. The implementation of the model in a Peruvian biofuels company, showed a cost reduction of around 11 % when compared to the current costs.

This paper deals with the problem of the optimal reconfiguration of medium voltage distribution networks by proposing a mixed-integer nonlinear programming (MINLP) model. This optimization model has as objective function the minimization of the total power losses in all the branches of the network constrained by active and reactive power balance equations, voltage regulation bounds and device capabilities, among others. The proposed MINLP formulation works with branch-to-node incidence that allows representing the active and reactive power flow in branches as a function of the real and imaginary parts of the voltages and currents. The solution of the MINLP model is reached through the general algebraic modeling system widely know as GAMS package by presenting it in a tutorial form. This software allows implementing in compact form the proposed model and solve it via branch and bound methods. Two test feeders composed by 5 and 14 nodes permits demonstrating the fidelity of the proposed MINLP model regarding power losses minimization when compared with literature reports.