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 f...
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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.
The development of a superior treatment option for severe acute malnutrition (SAM) which allowed for home-based therapy put in place constraints that are crucial for ensuring the feasibility and nutritional integrity ...
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The development of a superior treatment option for severe acute malnutrition (SAM) which allowed for home-based therapy put in place constraints that are crucial for ensuring the feasibility and nutritional integrity of the treatment. Soon after the initial success of ready-to-use therapeutic food (RUTF), there were attempts to modify the formulation for cost and other areas of acceptability. While alternative formulations have been taken on in clinical trials, they have been inferior to the standard RUTF recipe. linear programming (LP) technology, however, has streamlined the formulation process allowing the user to account for the crucial constraints required to maintain the feasibility and nutritional integrity of standard RUTF. With the aid of an LP tool and other functional tools for assessing nutrient quality, nutrition researchers can use innovative approaches in food development that could potentially revolutionize food aid products.
作者：
Yang, Y.US NRC
Off Res Two White Flint North 11545 Rockville Pike Rockville MD 20852 USA
Since the beginning of the development of interior-point methods, there exists a puzzling gap between the results in theory and the observations in numerical experience, i.e., algorithms with good polynomial bounds ar...
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Since the beginning of the development of interior-point methods, there exists a puzzling gap between the results in theory and the observations in numerical experience, i.e., algorithms with good polynomial bounds are not computationally efficient and algorithms demonstrated efficiency in computation do not have a good or any polynomial bound. Todd raised a question in 2002: Can we find a theoretically and practically efficient way to reoptimize? This paper is an effort to close the gap. We propose two arc-search infeasible interior-point algorithms with infeasible central path neighborhood wider than all existing infeasible interior-point algorithms that are proved to be convergent. We show that the first algorithm is polynomial and its simplified version has a complexity bound equal to the best known complexity bound for all (feasible or infeasible) interior-point algorithms. We demonstrate the computational efficiency of the proposed algorithms by testing all Netlib linear programming problems in standard form and comparing the numerical results to those obtained by Mehrotra's predictor-corrector algorithm and a recently developed more efficient arc-search algorithm (the convergence of these two algorithms is unknown). We conclude that the newly proposed algorithms are not only polynomial but also computationally competitive compared to both Mehrotra's predictor-corrector algorithm and the efficient arc-search algorithm.
Objective: Introduction of biofortified cassava as school lunch can increase vitamin A intake, but may increase risk of other deficiencies due to poor nutrient profile of cassava. We assessed the potential effect of i...
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Objective: Introduction of biofortified cassava as school lunch can increase vitamin A intake, but may increase risk of other deficiencies due to poor nutrient profile of cassava. We assessed the potential effect of introducing a yellow cassava-based school lunch combined with additional food-based recommendations (FBR) on vitamin A and overall nutrient adequacy using Optifood (linear programming tool). Design: Cross-sectional study to assess dietary intakes (24 h recall) and derive model parameters (list of foods consumed, median serving sizes, food and food (sub)group frequency distributions, food cost). Three scenarios were modelled, namely daily diet including: (i) no school lunch;(ii) standard 5 d school lunch with maize/beans;and (iii) 5 d school lunch with yellow cassava. Each scenario and scenario 3 with additional FBR were assessed on overall nutrient adequacy using recommended nutrient intakes (RNI). Setting: Eastern Kenya. Subjects: Primary-school children (n 150) aged 7-9 years. Results: Best food pattern of yellow cassava-based lunch scenario achieved 100% RNI for six nutrients compared with no lunch (three nutrients) or standard lunch (five nutrients) scenario. FBR with yellow cassava and including small dried fish improved nutrient adequacy, but could not ensure adequate intake of fat (52 % of average requirement), riboflavin (50% RNI), folate (59% RNI) and vitamin A (49% RNI). Conclusions: Introduction of yellow cassava-based school lunch complemented with FBR potentially improved vitamin A adequacy, but alternative interventions are needed to ensure dietary adequacy. Optifood is useful to assess potential contribution of a biofortified crop to nutrient adequacy and to develop additional FBR to address remaining nutrient gaps.
We study the intersection of finitely generated subgroups of free groups by utilizing the method of linear programming. We prove that if is a finitely generated subgroup of a free group F, then the WN-coefficient of i...
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We study the intersection of finitely generated subgroups of free groups by utilizing the method of linear programming. We prove that if is a finitely generated subgroup of a free group F, then the WN-coefficient of is rational and can be computed in deterministic exponential time in the size of . This coefficient is the minimal nonnegative real number such that, for every finitely generated subgroup of F, it is true that , where is the reduced rank of H, is the rank of H, and is the reduced rank of the generalized intersection of and . We also show the existence of a subgroup of F such that , the Stallings graph of has at most doubly exponential size in the size of and can be constructed in exponential time in the size of H-1.
This paper deals with a trajectory tracking model predictive control for a single mast stacker crane, which is used for automatic storage or retrieval of payloads in automated warehouses. The mathematical model of the...
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linear programming problems and System of linear equations have many applications in various science and engineering problems like network analysis, operations research etc. In general linear programming Problem (LPP)...
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linear programming problems and System of linear equations have many applications in various science and engineering problems like network analysis, operations research etc. In general linear programming Problem (LPP) and the system of linear equations contain crisp parameters that is real numbers or complex numbers as their coefficients and constants, but in real life applications, LPP and system of equations may contain the constrains or the parameters as uncertain. These uncertain values are not the exact real numbers but vary within some range of values, the values may vary within an interval or can be considered as fuzzy *** this paper, we have developed a new Ranking function (which converts the fuzzy number into crisp) to solve a fully fuzzy LPP and System of equations. Unlike the previous ranking functions, the proposed ranking function uses fuzzy number itself improving the accuracy of the solution. The ranking function is derived by replacing the non-parallel sides of the trapezoidal fuzzy number with non-linear functions. Various numerical examples are included and compared with the pre-existing methods.
In this paper we present models and optimization algorithms to rapidly compute the fuel-optimal energy management strategies of a hybrid electric powertrain for a given driving cycle. Specifically, we first identify a...
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In this paper we present models and optimization algorithms to rapidly compute the fuel-optimal energy management strategies of a hybrid electric powertrain for a given driving cycle. Specifically, we first identify a mixed-integer model of the system, including the engine on/off signal. Thereafter, by carefully relaxing the fuel-optimal control problem to a linear program, we devise an iterative algorithm to rapidly compute the minimum-fuel energy management strategies. We validate our approach by comparing its solution with the globally optimal one obtained solving the mixed-integer linear problem and demonstrate its effectiveness by assessing the impact of different battery charge targets on the achievable fuel consumption. Numerical results show that the proposed algorithm can assess fuel-optimal control strategies in a few seconds, paving the way for extensive parameter studies and real-time implementations.
The intended nationally determined contribution (INDC) of Vietnam to the 2015 United Nations Climate Change Conference (COP21) is a 25% reduction in greenhouse gas (GHG) emissions relative to the business-as-usual (BA...
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The intended nationally determined contribution (INDC) of Vietnam to the 2015 United Nations Climate Change Conference (COP21) is a 25% reduction in greenhouse gas (GHG) emissions relative to the business-as-usual (BAU) scenario by 2030. There are various measures proposed in the INDC, but studies to assess their potential effectiveness are still needed. An input-output based linear programming model is developed in this work to evaluate the maximum GHG emission reductions which can be achieved, given various climate change mitigation strategies. Six scenarios are considered to identify the highest GHG emission reduction that can be achieved by the year 2030. These scenarios include BAU, the consideration of two different levels of differentiated sector growth, the adoption of a low-carbon electricity mix, energy efficiency enhancement for final consumption, and energy efficiency enhancement in the agriculture, transport and waste sectors. Each scenario quantifies the sector final demand, sector gross output, sector GHG emission load and the impact on human health. Results show that the best strategy is to simultaneously implement all of the identified low-carbon measures, which achieves a 24.6% reduction in overall GHG emissions in comparison to BAU levels. (C) 2018 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
A trigeneration system consists of interdependent technologies for power generation, heat generation, and the generation of cooling effect which leads to the overall improved thermodynamic efficiency of the system. Ho...
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A trigeneration system consists of interdependent technologies for power generation, heat generation, and the generation of cooling effect which leads to the overall improved thermodynamic efficiency of the system. However, the optimal design of a trigeneration system also depends on the product price variability of the energy streams which are highly dependent on the price of the raw materials and the product demand. Taking into consideration expected price fluctuations of streams, it is then possible for plant owners and engineers to evaluate the investment risk associated with the design capacity of a trigeneration system. The study proposes the use of a 2 k factorial design of experiments together with fuzzy linear programming to conduct a price sensitivity analysis in the optimal design of a trigeneration system. This type of analysis can provide plant owners information on possible configurations for optimal capacity given uncertainty in the price parameters.
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