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OBJECTIVE: To estimate the lowest cost of a healthy and culturally acceptable diet and to assess the evolution of its cost in the periods 2008-2009 and 2017-2018. METHODS: We used data on the individual food consumption and food prices from the Pesquisas de Orçamentos Familiares (Household Budget Surveys), in the 2008-2009 and 2017-2018. The sample strata of each period were aggregated, forming 108 new strata with geographic and economic homogeneity. Linear programming models generated diets for each new stratum, considering the constraints in two models: model 1 (≥ 400g of fruits and vegetables); and model 2 (≥ 400g of fruits and vegetables, < 2300mg of sodium, sodium/potassium ratio < 1, ≥ 500mg of calcium). Each food could progressively deviate 5g from the observed consumption averages until the models found a solution in each of the strata. The objective function was to minimize the total cost of the diet. RESULTS: The average observed and optimized costs were R$4.96, R$4.62 (model 1) and R$5.08 (model 2) in 2008-2009, and R$9.18, R$8.69 and R$9.87 in 2017-2018. Models 1 and 2 resulted in an increase of up to 6% and 11% in 2008-2009, and of up to 25% and 34% in 2017-2018 in the lowest income strata. The main changes observed in the two models include the reduction in the amounts of sweetened beverages, sweets, sauces, ready-to-eat foods, and an increase in fruits and vegetables, flour, and tubers. CONCLUSION: The adequate amount of fruits and vegetables resulted in an increase in costs to some population strata. When the adequacy of calcium, sodium, and potassium was considered, we observed a more significant increase in cost, especially in 2017-2018.

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The cell expresses various genes in specific contexts with respect to internal and external perturbations to invoke appropriate responses. Transcription factors (TFs) orchestrate and define the expression level of genes by binding to their regulatory regions. Dysregulated expression of TFs often leads to aberrant expression changes of their target genes and is responsible for several diseases including cancers. In the last two decades, several studies experimentally identified target genes of several TFs. However, these studies are limited to a small fraction of the total TFs encoded by an organism, and only for those amenable to experimental settings. Experimental limitations lead to many computational techniques having been proposed to predict target genes of TFs. Linear modeling of gene expression is one of the most promising computational approaches, readily applicable to the thousands of expression datasets available in the public domain across diverse phenotypes. Linear models assume that the expression of a gene is the sum of expression of TFs regulating it. In this chapter, I introduce mathematical programming for the linear modeling of gene expression, which has certain advantages over the conventional statistical modeling approaches. It is fast, scalable to genome level and most importantly, allows mixed integer programming to tune the model outcome with prior knowledge on gene regulation.

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Genes are transcribed into various RNA molecules, and a portion of them called messenger RNA (mRNA) is then translated into proteins in the process known as gene expression. Gene expression is a high-energy demanding process, and aberrant expression changes often manifest into pathophysiology. Therefore, gene expression is tightly regulated by several factors at different levels. MicroRNAs (miRNAs) are one of the powerful post-transcriptional regulators involved in key biological processes and diseases. They inhibit the translation of their mRNA targets or degrade them in a sequence-specific manner, and hence control the rate of protein synthesis. In recent years, in response to experimental limitations, several computational methods have been proposed to predict miRNA target genes based on sequence complementarity and structural features. However, these predictions yield a large number of false positives. Integration of gene and miRNA expression data drastically alleviates this problem. Here, I describe a mathematical linear modeling approach to identify miRNA targets at the genome scale using gene and miRNA expression data. Mathematical modeling is faster and more scalable to genome-level compared to conventional statistical modeling approaches.

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BACKGROUND: Food cost and affordability is one of the main barriers to improve the nutritional quality of diets of the population. However, in Argentina, where over 60% of adults and 40% of children and adolescents are overweight or obese, little is known about the difference in cost and affordability of healthier diets compared to ordinary, less healthy ones. METHODS: We implemented the "optimal approach" proposed by the International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support (INFORMAS). We modelled the current diet and two types of healthy diets, one equal in energy with the current diet and one 6.3% lower in energy by linear programming. Cost estimations were performed by collecting food product prices and running a Monte Carlo simulation (10,000 iterations) to obtain a range of costs for each model diet. Affordability was measured as the percentage contribution of diet cost vs. average household income in average, poor and extremely poor households and by income deciles. RESULTS: On average, households must spend 32% more money on food to ensure equal energy intake from a healthy diet than from a current model diet. When the energy intake target was reduced by 6.3%, the difference in cost was 22%. There are no reasonably likely situations in which any of these healthy diets could cost less or the same than the current unhealthier one. Over 50% of households would be unable to afford the modelled healthy diets, while 40% could not afford the current diet. CONCLUSIONS: Differential cost and affordability of healthy vs. unhealthy diets are germane to the design of effective public policies to reduce obesity and NCDs in Argentina. It is necessary to implement urgent measures to transform the obesogenic environment, making healthier products more affordable, available and desirable, and discouraging consumption of nutrient-poor, energy-rich foods.

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The aim was to design culturally acceptable and healthy diets with reduced energetic share of ultra-processed foods (UPF%) at no cost increment and to evaluate the impact of the change in the UPF% on diet quality. Food consumption and price data were obtained from the Household Budget Survey (n 55 970 households) and National Dietary Survey (n 32 749 individuals). Linear programming models were performed to design diets in which the mean population UPF% was reduced up to 5 % with no cost increment relative to the observed costs. The models were isoenergetic or allowed the energy content to vary according to the UPF%, and they were not constrained to nutritional goals (nutrient-free models) or maximised the compliance with dietary recommendations (nutrient-constrained models). Constraints regarding food preference were introduced in the models to obtain culturally acceptable diets. The mean population UPF% was 23·8 %. The lowest UPF% attained was approximately 10 %. The optimised diet cost was up to 20 % cheaper than the observed cost, depending on the model and the income level. In the optimised diets, the reduction in the UPF% was followed by an increase in fruits, vegetables, beans, tubers, dairy products, nuts, fibre, K, Mg, vitamin A and vitamin C in the nutrient-constrained models, compared with the observed consumption in the population. There was little variation in most nutrients across the UPF% reduction. The UPF% reduction in the nutrient-free models impacted only trans-fat and added sugar content. UPF% reduction and increase in diet quality are possible at no cost increment.

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As modificações no padrão alimentar brasileiro necessárias para atender as recomendações nutricionais no país envolvem o aumento no consumo de alimentos frescos e minimamente processados. Estes alimentos são uma das principais fontes de resíduos de agrotóxicos na alimentação e são usualmente monitorados quanto a sua conformidade às Boas Práticas Agrícolas, que é mensurada pelo Limite Máximo de Resíduos de agrotóxicos legislados por quilo de alimento. Desta forma, os objetivos deste estudo foram: (i) identificar mudanças na dieta Brasileira necessárias para alcançar a adequação nutricional, considerando as preferências de consumo, sem exceder os níveis de segurança de exposição crônica a agrotóxicos; e (ii) verificar se dietas com alimentos adequados às Boas Práticas Agrícolas são seguras de acordo com a Ingestão Diária Aceitável para agrotóxicos na população brasileira. Para isto, os dados de consumo de alimentos de 46.164 indivíduos, amostrados pela Pesquisa de Orçamentos Familiares de 2017 a 2018, foi combinado aos dados de resíduos de agrotóxicos de 28 alimentos, com mais de 10 mil amostras coletadas nas capitais brasileiras, do Programa de Análise de Resíduo de Agrotóxicos (PARA); e aos dados de Limites Máximos de Resíduos de agrotóxico por alimento da Agência Nacional de Vigilância Sanitária. A amostra foi estratificada por estados brasileiros e por níveis de renda, gerando 108 estratos. Para o objetivo (i), três modelos de programação linear, que minimizaram o custo da dieta em cada estrato, foram elaborados: (1) restrições de preferências alimentar e quantidades mínimas de energia, macronutrientes, vitaminas e minerais; (2) modelo 1 + Ingestão Diária Aceitável de resíduos de agrotóxicos (IDA); e (3) modelo 1 + nível atual de exposição a resíduos de agrotóxicos. No modelo 1, todas as restrições nutricionais foram atendidas sem exceder o IDA para nenhum dos 228 resíduos avaliados, embora a exposição tenha aumentado entre as dietas otimizadas no modelo 1 e seus níveis observados. No modelo 3, não foi possível atender simultaneamente as restrições nutricionais e as de segurança crônica para agrotóxico. Para o objetivo (ii), dois modelos de programação linear, que minimizaram o custo da dieta em cada estrato, foram elaborados com as mesmas restrições (1) e (2) impostas ao objetivo (i). No modelo 1, todas as restrições nutricionais foram atendidas, no entanto, os níveis de exposição aos agrotóxicos excederam o ADI. No modelo 2, não foi possível atender às restrições de segurança crônica para agrotóxicos com os Limites Máximos de Resíduos legislados no país. As principais mudanças alimentares necessárias para atingir as recomendações nutricionais foram: aumentar as quantidades de frutas, vegetais, laticínios e frutos do mar; e reduzir o arroz, a carne vermelha e as bebidas adoçadas com açúcar. Em conclusão, atender as recomendações nutricionais aumenta a exposição a resíduos de agrotóxicos em comparação aos níveis observados na dieta brasileira, sem exceder seu IDA para exposição crônica; e alimentos considerados adequados às Boas Práticas Agrícolas não oferecem níveis seguros de exposição crônica de agrotóxicos para o Brasil.

The changes in the Brazilian dietary pattern necessary to meet nutritional recommendations involve an increase in the consumption of fresh and minimally processed foods. These foods are one of the major sources of pesticide residues on diets and are usually monitored by its compliance with Good Agriculture Practice, which is measured by the Maximum Residue Limits parameter legislated per kilo of pesticide in foods. Therefore, the objectives of this study are: (i) to identify changes in the current diet to achieve nutritional adequacy without exceeding the chronic safety levels of pesticide exposure considering regional food consumption preferences; and (ii) to verify if diets comprising foods that are adequate according to the Good Agriculture Practice are also safe according to the Acceptable Daily Intake of pesticide residues in the Brazilian population. Food consumption data from the National Dietary Survey 2017-2018 (n=46.164 individuals) were linked to the pesticide residues database from the Program on Pesticide Residue Analysis in Food, and to the Maximum Residue Limits of pesticides per food data from the National Health Surveillance Agency. The sample was stratified by Brazilian states and by income levels, totaling 108 strata. For objective (i), three linear programming models, which minimized diet cost within strata, were performed by: (1) food preferences and minimum requirement of energy, macronutrients, vitamins and mineral restrictions; (2) Model 1 + Acceptable Daily Intake of pesticides residues; and (3) model 1 + observed levels of pesticide exposure. In model 1, all the nutritional constraints were met without exceeding the ADI for none of the 228 residues assessed, although the exposure significantly increased between the optimized diets in model 1 and its observed levels. In model 3, it was infeasible to keep the current levels of pesticide residue exposure while meeting all the nutritional constraints. For objective (ii), two linear programming models, which minimized diet cost, were performed applying the same restrictions (1) and (2) from objective (i). In model 1, all the nutritional constraints were met, but pesticide exposure levels exceeded the ADI. In model 2, it was not possible to meet chronic safety constraints for pesticides with the Maximum Residue Limit limits legislated in the country. The main dietary changes needed to achieve the nutritional constraints were: increase fruit and vegetables, dairy, and seafood quantities; and reduce rice, red meat, and sugar-sweetened beverages. In conclusion, meeting nutritional adequacy increases pesticide exposure compared to the observed diets, without exceeding its ADI for chronic exposure; and foods within the Good Agriculture Practice do not guaranty safe levels of chronic exposure to pesticides for Brazil.

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ABSTRACT OBJECTIVE To estimate the lowest cost of a healthy and culturally acceptable diet and to assess the evolution of its cost in the periods 2008-2009 and 2017-2018. METHODS We used data on the individual food consumption and food prices from the Pesquisas de Orçamentos Familiares (Household Budget Surveys), in the 2008-2009 and 2017-2018. The sample strata of each period were aggregated, forming 108 new strata with geographic and economic homogeneity. Linear programming models generated diets for each new stratum, considering the constraints in two models: model 1 (≥ 400g of fruits and vegetables); and model 2 (≥ 400g of fruits and vegetables, < 2300mg of sodium, sodium/potassium ratio < 1, ≥ 500mg of calcium). Each food could progressively deviate 5g from the observed consumption averages until the models found a solution in each of the strata. The objective function was to minimize the total cost of the diet. RESULTS The average observed and optimized costs were R$4.96, R$4.62 (model 1) and R$5.08 (model 2) in 2008-2009, and R$9.18, R$8.69 and R$9.87 in 2017-2018. Models 1 and 2 resulted in an increase of up to 6% and 11% in 2008-2009, and of up to 25% and 34% in 2017-2018 in the lowest income strata. The main changes observed in the two models include the reduction in the amounts of sweetened beverages, sweets, sauces, ready-to-eat foods, and an increase in fruits and vegetables, flour, and tubers. CONCLUSION The adequate amount of fruits and vegetables resulted in an increase in costs to some population strata. When the adequacy of calcium, sodium, and potassium was considered, we observed a more significant increase in cost, especially in 2017-2018.

RESUMO OBJETIVO Estimar o menor custo de uma alimentação saudável e culturalmente aceitável e avaliar a evolução de seu custo nos períodos de 2008-2009 e 2017-2018. MÉTODOS Foram utilizados dados de consumo individual dos módulos de consumo alimentar das Pesquisas de Orçamentos Familiares de 2008-2009 e 2017-2018. Os preços dos alimentos foram obtidos do módulo de caderneta de despesa das respectivas pesquisas. Os estratos amostrais de cada período foram reagrupados, formando 108 novos estratos com homogeneidade geográfica e econômica. Modelos de programação linear foram elaborados para gerar dietas para cada novo estrato, considerando as restrições do modelo 1 (≥ 400g de frutas e hortaliças) e modelo 2 (≥ 400g de frutas e hortaliças, < 2300mg de sódio, relação sódio/potássio < 1, ≥ 500mg de cálcio). Cada alimento das dietas observadas poderia desviar progressivamente em 5g a partir das médias de consumo observadas até que os modelos encontrassem uma solução em cada um dos estratos. A função objetivo foi de minimizar o custo total da dieta. RESULTADOS Os custos médios observados e otimizados foram de R$4,96, R$4,62 (modelo 1) e R$5,08 (modelo 2) em 2008-2009 e de R$9,18, R$8,69 e R$9,87 em 2017 -2018. Nos modelos 1 e 2 ocorreram incrementos de até 6% e 11% em 2008-2009 e de até 25% e 34% em 2017-2018 na menor faixa de renda. As principais modificações observadas nos dois modelos incluem a redução nas quantidades de bebidas adoçadas, doces, molhos, alimentos prontos para consumo e aumento de frutas e hortaliças, farinhas e tubérculos. CONCLUSÃO A adequação da quantidade de frutas e hortaliças acarretou aumento no custo para parte da população. Quando a adequação de cálcio, sódio e potássio foram consideradas, ocorreu um aumento mais expressivo no custo, especialmente em 2017-2018.

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This paper employs a solution to the agent-guidance problem in an environment with obstacles, whose avoidance techniques have been extensively used in the last years. There is still a gap between the solution times required to obtain a trajectory and those demanded by real world applications. These usually face a tradeoff between the limited on-board processing performance and the high volume of computing operations demanded by those real-time applications. In this paper we propose a deferred decision-based technique that produces clusters used for obstacle avoidance as the agent moves in the environment, like a driver that, at night, enlightens the road ahead as her/his car moves along a highway. By considering the spatial and temporal relevance of each obstacle throughout the planning process and pruning areas that belong to the constrained domain, one may relieve the inherent computational burden of avoidance. This strategy reduces the number of operations required and increases it on demand, since a computationally heavier problem is tackled only if the simpler ones are not feasible. It consists in an improvement based solely on problem modeling, which, by example, may offer processing times in the same order of magnitude than the lower-bound given by the relaxed form of the problem.

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The improvement of diets from a nutritional and health perspective has been a critical policy objective in developing nations for the past few decades. However, the current stress that human populations are exerting on the planet has made it important to assess diets using environmental indicators, such as greenhouse gas (GHG) emissions. Therefore, the main objective of the current study was to propose a methodology in which Life Cycle Assessment results linked to dietary patterns in Peru were combined with nutritional and economic data to optimize diets. For this, a linear programming model was built in which the environmental, nutritional and economic information on a set of 25 dietary patterns in Peru were optimized in order to achieve the environmentally best-performing diet that complies with economic and nutritional standards. The result of the proposed linear program allowed understanding the amount of each individual food product that should be consumed in each city that satisfies all the restrictions included in the model in order to attain the lowest GHG emissions possible. Results demonstrated that GHG reductions in food diets can be attained through optimization. For instance, in the case of Lima the obtained reduction was 6%, lowering the annual per capita footprint linked to food diets to 690 kg CO2eq, as compared to the current value of 736 kg CO2eq. From an economic perspective, results show that there are important disparities between cities in terms of increasing or decreasing prices of the market basket. Considering that in most areas of the country food purchase accounts for approximately 50% of household expenditure, it is plausible to assume that food choice is a main carrier to achieve GHG emission mitigations. In this context, the method constitutes a useful tool for policy-makers to push forward joint regulations to improve health-related issues linked to the food diet and food choice together with recommendations to lower the climatic impact of diets.

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The mining industry is one of the world's massive scrap off-the-road (OTR) tire generators. Reverse logistics (RL) allows for a cost-effective treatment of residual items with environmentally friendly practices. This paper aims to design a RL network for large OTR tires discarded from scattered mining sites, which requires a substantial initial investment in tire downsizing equipment. Therefore, the on-site use of a single shared shredding resource set is proposed with a schedule of visits between mines. Our contribution is a mixed-integer linear programming model set to determine the OTR tires optimal network, including decisions regarding a tire-fuelled power plant location, tire shredding and transport amounts, and a shredding resource set schedule to maximize the profits of the RL network while considering whole waste tire stockpile limits per year. Results showed that the proposed RL network starting from mine shredding tires and supplying a power generation plant might be a profitable solution that could help mines to comply with the legal regulations and turn this waste into a positive economic value good. Environmental and social implications are the mitigation of scrap tires, an increased job demand triggered by power plants, and public health improvement in the vicinity of the mining sites.

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BACKGROUND: Meeting nutrient intake recommendations may demand substantial modifications in dietary patterns, and may increase diet cost. Incentives for modifying one's dietary intake that disregard prices are unlikely to be effective in the general population, especially among low-income strata, due to the high percentage of income committed to food purchases. The aim of this study is to evaluate how much the nutrient content can be increased through a modeled diet, without any cost increase, for low-income Brazilian households. METHODS: Low-income households were selected from the Household Budget Survey (24,688 households) and National Dietary Survey (6,032 households, 16,962 individuals), from where we obtained food prices and consumption data. Food quantities were modeled using linear programming to find diets that meet nutritional recommendations in two sets of models: cost-constrained (the cost should not be higher than the observed diet cost) and cost-free. Minimum and maximum amounts of each food in the modelled diets were allowed at three levels of food acceptability: rigorous (least deviance from the current observed diets), moderate, and flexible (higher deviance from the current observed diets). RESULTS: We found no feasible solution that would accommodate all the nutritional targets. The most frequent limiting nutrients were calcium; vitamins D, E, and A; zinc; fiber; sodium; and saturated and trans-fats. However, increases in nutrient contents were observed, especially for fiber, calcium, copper, magnesium, vitamin A, vitamin C, and vitamin E. In general, the best achievement was obtained with cost-free models. Fruits and beans increased in all models; large increase in whole cereals was observed only in the flexible models; large increase in vegetables was observed only in the cost-free models; and fish increased only in the cost-free models. Reductions were observed for rice, red and processed meats, sugar-sweetened beverages, and sweets. The mean observed cost was US$2.16 per person/day. The mean cost in the cost-free models was US$2.90 (moderate), US$2.70 (rigorous), and US$2.60 (flexible). CONCLUSION: The complete nutritional adequacy is unattainable, although feasible changes would substantially improve diet quality by improving nutrient content without additional costs.

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ABSTRACT The aim of this work was to improve sweet bread (R1) nutritionally by partially replacing the wheat flour with other non-traditional flours through linear programming. Chemical Score, lipid profile, microbiological quality and acceptability were determined. Both recipes, R2 and R3, were formulated according to the Dietary Guidelines for Americans; and R3 according to the maximum amounts of flours that impart negative sensory attributes, as well. The resulting proportions were: wheat/broad bean/chia/ amaranth flours 64/22/13/0 (R2) and 83/2/4/11 (R3). The obtained products presented adequate contributions of proteins and lipids, while fiber increased significantly. The Chemical Score increased from 46% (R1) to 95% (R2) and to 91% (R3) respectively, and the fatty acids ratio ω3: ω6 improved. R2 was not sensorially accepted while R3 presented high acceptability in adults and school-aged children. Recipe R3 could be included in school menus to improve children's nutritional status.

RESUMEN El objetivo de este trabajo fue mejorar nutricionalmente un pan dulce (R1), reemplazando parcialmente la harina de trigo con otras harinas no tradicionales a través de la programación lineal. Se determinó la puntuación química, el perfil lipídico, la calidad microbiológica y la aceptabilidad. Ambas recetas enriquecidas nutricionalmente, R2 y R3, se formularon de acuerdo a pautas dietéticas estadounidenses; y para R3, además, se tuvieron en cuenta las cantidades máximas de harinas que imparten atributos sensoriales negativos. Las proporciones resultantes fueron harina de trigo/haba/chía/amaranto 64/22/13/0 (R2) y 83/2/4/11 (R3). Los productos obtenidos presentaron contenidos adecuados de proteínas y lípidos, mientras que la fibra aumentó significativamente. La puntuación química aumentó de 46% (R1) a 95% (R2) y a 91% (R3) respectivamente, y la relación de ácidos grasos ω3: ω6 mejoró. R2 no fue aceptado sensorialmente, mientras que R3 presentó alta aceptabilidad en adultos y niños en edad escolar. La receta R3 podría incluirse en los menús escolares para mejorar el estado nutricional de los niños.

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This article discusses the configuration of specialized healthcare networks and aims to analyze the potential for optimization of geographic access in the chemotherapy network of the Brazilian Unified National Health System (SUS) in Rio Grande do Sul State, Brazil, using linear programming. The study used ex post facto mathematical modeling with an analytical objective and a qualitative-quantitative approach, using data collection and literature and document searches as the procedures. The potential for optimization was assessed by the percentage difference between the total distances traveled under the current situation and the optimum solution obtained. The results with the optimized situation included a decrease of 293,246km (14.4%) in the total monthly distance traveled in the network, or a mean reduction of 13.02km per procedure performed, compared to the current distance traveled. This gain would be obtained by redistribution of the municipalities of origin and the referral services' capacity to supply procedures. The results point to great potential for optimization of the target network, proving that linear programming can provide technical support for the configuration of new specialized thematic healthcare networks and optimization of the existing networks.

Este artigo discute a conformação de redes temáticas de atenção à saúde e tem como objetivo analisar o potencial de otimização do acesso geográfico na rede de quimioterapia do Sistema Único de Saúde (SUS), no Estado do Rio Grande do Sul, Brasil, com o uso de programação linear. Trata-se de um estudo de modelagem matemática ex post facto, com objetivo analítico e abordagem qualiquantitativa, que utilizou como procedimentos de coleta a pesquisa bibliográfica e documental. O potencial de otimização foi avaliado pela diferença percentual entre os somatórios das distâncias percorridas na rede para a situação atual e para a solução ótima obtida. Entre os resultados identificados na situação otimizada estão a diminuição de 293.246km (14,4%) na distância total mensal percorrida na rede, correspondendo a uma redução média de 13,02km por procedimento realizado, se comparada com a atual distância percorrida, a ser obtida pela redistribuição dos municípios de origem e das capacidades de oferta de procedimentos pelos serviços de referência. Esses resultados indicam a existência de grande potencial de otimização na rede estudada, comprovando que o uso da programação linear pode oferecer suporte técnico ao processo de conformação de novas redes temáticas de atenção à saúde e à otimização daquelas existentes.

Este artículo discute la conformación de redes temáticas de atención a la salud, y tiene como objetivo analizar el potencial de optimización del acceso geográfico a la red de quimioterapia del Sistema Único de Salud (SUS), en el Estado de Río Grande do Sul, Brasil, con el uso de una programación lineal. Se trata de un estudio de modelado matemático ex post facto, con un objetivo analítico y enfoque cuali-cuantitativo, que utilizó como procedimientos de recogida la investigación bibliográfica y documental. El potencial de optimización se evaluó por la diferencia de porcentaje entre las sumas de las distancias recorridas en la red para la situación actual y para la solución óptima obtenida. Entre los resultados identificados en la situación optimizada están la disminución de 293.246km (14,4%) en la distancia total mensual recorrida en la red, correspondiendo a una reducción media de 13,02km por procedimiento realizado, si se compara con la actual distancia recorrida, que debe ser obtenida por la redistribución de los municipios de origen y de las capacidades de oferta de procedimientos por los servicios de referencia. Estos resultados indican la existencia de un gran potencial de optimización en la red estudiada, comprobando que el uso de la programación lineal puede ofrecer apoyo técnico al proceso de conformación de nuevas redes temáticas de atención a la salud y a la optimización de las ya existentes.

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The application of optimization methods to forest management has given rise to a successful line of investigation in recent decades. However, there have been few publications associated with the application of these techniques to the management of industrial forest plantations (those with short or medium rotations, always less than 50 years), which consider the important role played by these forest systems in the supply of diverse goods and services. This study presents an overview of this literature which, by analyzing 67 articles published in journals contained in the ISI Web of Science, highlight, among other aspects, the techniques employed, their evolution, their planning type (strategic, tactical or operational), the functional objectives and constraints considered, or the type of software deployed in these studies. The results show how Model I has been the one most frequently used in these studies, and how the spatial component is increasing in importance. However, classic optimization methods, such as mixed integer programming, have been those most commonly resorted to, although the employment of multi-criteria techniques such as goal programming and analytic hierarchical process have strongly emerged in recent years.(AU)

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The application of optimization methods to forest management has given rise to a successful line of investigation in recent decades. However, there have been few publications associated with the application of these techniques to the management of industrial forest plantations (those with short or medium rotations, always less than 50 years), which consider the important role played by these forest systems in the supply of diverse goods and services. This study presents an overview of this literature which, by analyzing 67 articles published in journals contained in the ISI Web of Science, highlight, among other aspects, the techniques employed, their evolution, their planning type (strategic, tactical or operational), the functional objectives and constraints considered, or the type of software deployed in these studies. The results show how Model I has been the one most frequently used in these studies, and how the spatial component is increasing in importance. However, classic optimization methods, such as mixed integer programming, have been those most commonly resorted to, although the employment of multi-criteria techniques such as goal programming and analytic hierarchical process have strongly emerged in recent years.

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Reduced-impact logging is a well known practice applied in most sustainable forest management plans in the Amazon. Nevertheless, there are still ways to improve the operational planning process. Therefore, the aim of this study was to create an integer linear programming (ILP) to fill in the knowledge gaps in the decision support system of reduced impact logging explorations. The minimization of harvest tree distance to wood log landing was assessed. Forest structure aspects, income and wood production were set in the model, as well as the adjacency constraints. Data are from a dense ombrophylous forest in the western Brazilian Amazon. We applied the phytosociological analysis and BDq method to define the selective logging criteria. Then, ILP models were formulated to allow the application of the constraints. Finally, 32 scenarios (unbalanced forest, UF, and balanced forest, BF) were generated and compared with real executed plans (RE). Robust results were achieved and the expected finding of each scenario was met. The feasibility to integrate ILP models in uneven-aged forest management projects was endorsed. Consequently, the UF and BF scenarios tested were efficient and concise, introducing new advances for forest management plans in the Amazon. The proposed models have a high potential to improve the selective logging activities in the Amazon forest.(AU)

A exploração de impacto reduzido é uma prática bem conhecida e aplicada na maioria dos planos de manejo florestal sustentável na Amazônia. Todavia, ainda há a possibilidade de melhoria do processo de planejamento da operação. Diante da falta de métodos auxiliares à tomada de decisão, o objetivo do trabalho foi desenvolver modelos de programação linear inteira (PLI) para suprir esta demanda. Considerou-se a minimização da distância entre as árvores exploradas e os pátios de estocagem de madeira. Aspectos estruturais, econômicos e produtivos foram incorporados ao modelo, bem como restrições de adjacência. Os dados derivam de uma floresta ombrófila densa na Amazônia Ocidental. Previamente, utilizou-se uma análise fitossociológica e o método BDq como critério de remoção. Posteriormente, modelos de PLI foram formulados para exemplificar as aplicações. Finalmente, 32 cenários (para floresta desbalaceada, UF, e floresta balanceada, BF) foram gerados e comparados com o plano executado no campo (RE). Resultados robustos foram obtidos e atenderam às expectativas de cada cenário. A viabilidade da integração dos modelos de PLI em projetos de manejo de florestas ineqüiâneas foi testado. Os cenários UF e BF testados foram eficientes e concisos, confirmando seu potencial para aumentar a eficiência de planos de exploração madeireira e manejo florestal na Amazônia.(AU)

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OBJECTIVE: To identify optimal food choices that meet nutritional recommendations to reduce prevalence of inadequate nutrient intakes. DESIGN: Linear programming was used to obtain an optimized diet with sixty-eight foods with the least difference from the observed population mean dietary intake while meeting a set of nutritional goals that included reduction in the prevalence of inadequate nutrient intakes to ≤20 %. SETTING: Brazil. SUBJECTS: Participants (men and women, n 25 324) aged 20 years or more from the first National Dietary Survey (NDS) 2008-2009. RESULTS: Feasible solution to the model was not found when all constraints were imposed; infeasible nutrients were Ca, vitamins D and E, Mg, Zn, fibre, linolenic acid, monounsaturated fat and Na. Feasible solution was obtained after relaxing the nutritional constraints for these limiting nutrients by including a deviation variable in the model. Estimated prevalence of nutrient inadequacy was reduced by 60-70 % for most nutrients, and mean saturated and trans-fat decreased in the optimized diet meeting the model constraints. Optimized diet was characterized by increases especially in fruits (+92 g), beans (+64 g), vegetables (+43 g), milk (+12 g), fish and seafood (+15 g) and whole cereals (+14 g), and reductions of sugar-sweetened beverages (-90 g), rice (-63 g), snacks (-14 g), red meat (-13 g) and processed meat (-9·7 g). CONCLUSION: Linear programming is a unique tool to identify which changes in the current diet can increase nutrient intake and place the population at lower risk of nutrient inadequacy. Reaching nutritional adequacy for all nutrients would require major dietary changes in the Brazilian diet.

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Este artigo discute a conformação de redes temáticas de atenção à saúde e tem como objetivo analisar o potencial de otimização do acesso geográfico na rede de quimioterapia do Sistema Único de Saúde (SUS), no Estado do Rio Grande do Sul, Brasil, com o uso de programação linear. Trata-se de um estudo de modelagem matemática ex post facto, com objetivo analítico e abordagem qualiquantitativa, que utilizou como procedimentos de coleta a pesquisa bibliográfica e documental. O potencial de otimização foi avaliado pela diferença percentual entre os somatórios das distâncias percorridas na rede para a situação atual e para a solução ótima obtida. Entre os resultados identificados na situação otimizada estão a diminuição de 293.246km (14,4%) na distância total mensal percorrida na rede, correspondendo a uma redução média de 13,02km por procedimento realizado, se comparada com a atual distância percorrida, a ser obtida pela redistribuição dos municípios de origem e das capacidades de oferta de procedimentos pelos serviços de referência. Esses resultados indicam a existência de grande potencial de otimização na rede estudada, comprovando que o uso da programação linear pode oferecer suporte técnico ao processo de conformação de novas redes temáticas de atenção à saúde e à otimização daquelas existentes.

This article discusses the configuration of specialized healthcare networks and aims to analyze the potential for optimization of geographic access in the chemotherapy network of the Brazilian Unified National Health System (SUS) in Rio Grande do Sul State, Brazil, using linear programming. The study used ex post facto mathematical modeling with an analytical objective and a qualitative-quantitative approach, using data collection and literature and document searches as the procedures. The potential for optimization was assessed by the percentage difference between the total distances traveled under the current situation and the optimum solution obtained. The results with the optimized situation included a decrease of 293,246km (14.4%) in the total monthly distance traveled in the network, or a mean reduction of 13.02km per procedure performed, compared to the current distance traveled. This gain would be obtained by redistribution of the municipalities of origin and the referral services' capacity to supply procedures. The results point to great potential for optimization of the target network, proving that linear programming can provide technical support for the configuration of new specialized thematic healthcare networks and optimization of the existing networks.

Este artículo discute la conformación de redes temáticas de atención a la salud, y tiene como objetivo analizar el potencial de optimización del acceso geográfico a la red de quimioterapia del Sistema Único de Salud (SUS), en el Estado de Río Grande do Sul, Brasil, con el uso de una programación lineal. Se trata de un estudio de modelado matemático ex post facto, con un objetivo analítico y enfoque cuali-cuantitativo, que utilizó como procedimientos de recogida la investigación bibliográfica y documental. El potencial de optimización se evaluó por la diferencia de porcentaje entre las sumas de las distancias recorridas en la red para la situación actual y para la solución óptima obtenida. Entre los resultados identificados en la situación optimizada están la disminución de 293.246km (14,4%) en la distancia total mensual recorrida en la red, correspondiendo a una reducción media de 13,02km por procedimiento realizado, si se compara con la actual distancia recorrida, que debe ser obtenida por la redistribución de los municipios de origen y de las capacidades de oferta de procedimientos por los servicios de referencia. Estos resultados indican la existencia de un gran potencial de optimización en la red estudiada, comprobando que el uso de la programación lineal puede ofrecer apoyo técnico al proceso de conformación de nuevas redes temáticas de atención a la salud y a la optimización de las ya existentes.

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En administración, se pueden presentar dos tipos de problemas de toma de decisiones: los que se solucionan en condiciones de certeza, es decir, libre de riesgo al optar por una solución, y los que dependen de la probabilidad de ocurrencia de eventos para poder tomar una decisión. En este último caso, aparecen con gran regularidad problemas de toma de decisiones en condiciones de conflicto, conocidos como teoría de juegos; como por ejemplo la adquisición de recursos informáticos, en el que la decisión de invertir en un recurso y no en otro adquiere mayor relevancia, en función de sus altos precios, y su gran demanda en cualquier rama de la sociedad. En la Facultad de Tecnología de la Universidad de Ciencias Médicas de Santiago de Cuba, se modeló el proceso de compras de estos recursos, a través de esta teoría, al no contar con opciones científicamente probadas hasta ese momento, que reportasen el mayor beneficio a la hora de adquirirlos cualquiera sea la plataforma informática. Por ello el objetivo de este trabajo es determinar desde el enfoque de la programación lineal, y específicamente la Teoría de Juegos, la estrategia óptima que bajo ciertas condiciones permitan conducir el proceso de adquisición de recursos informáticos. Como resultado se obtuvo una solución óptima, en la que se recomendaba invertir solamente en hardware para estaciones de trabajo, así como en hardware y componentes de red; lo que garantizaría la mejor forma de adaptación de los recursos invertidos, sin importar cuál sea la plataforma informática(AU)

In administration, two types of decision-making problems can be presented: those that are solved in conditions of certainty, that is, free of risk when opting for a solution, and those that depend on the probability of occurrence of events to be able to make a decision. In the last case, problems of decision-making in conditions of conflict, known as game theory, appear with great regularity; such as the purchase of computing resources, in which the decision to invest in one resource and not in another acquires greater relevance, due to its high prices and its high demand in any branch of society. In the Faculty of Technology of the University of Medical Sciences of Santiago de Cuba, the process of purchasing these resources was modeled through this theory, as it did not count with scientifically proved options until that moment, which reported the greatest benefit when purchasing them whatever the computing platform. Therefore, the objective of this work was to determine from the linear programming approach, and specifically the Games Theory, the optimal strategy that, under certain conditions, allows conducting the process of acquisition of computing resources. As a result, an optimal solution was obtained, which recommended investing only in hardware for workstations, and in hardware and network components; which would guarantee the best form of adaptation of the resources invested, no matter what the computing platform(AU)

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OBJECTIVE: To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS: Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS: The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS: The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

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