The objective of this paper is to study the linear programming algorithm of the mathematical model of agricultural machinery allocation when there are many farmland projects and cross operations. In this paper, combin...
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The objective of this paper is to study the linear programming algorithm of the mathematical model of agricultural machinery allocation when there are many farmland projects and cross operations. In this paper, combined with the mechanization process of crops in XPCC, the linear programming algorithm of mathematical model was used to establish the allocation scheme of different scales. All equations were solved and analyzed, and the allocation schemes of different planting scales were compared. It is also observed that through the interactive conflicts in between multiple objectives a solution vector can be analyzed. The results show that the activity cost of Scheme 5 was the lowest, only 1,260 yuan per mu, which was the best way to equip agricultural machinery. The results present that it is of great significance to optimize the configuration of agricultural machinery. The experimental results present that the portion of water which is reused in comparison with the total water is gradually increasing which leads to the overall reduction in water consumption.
The aim of this paper is to introduce a simplified presentation of a new computing procedure for solving trapezoidal neutrosophic linear programming (TrNLP) problem under uncertainties. Therefore, we firstly define th...
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Deep learning has received much attention lately due to the impressive empirical performance achieved by training algorithms. Consequently, a need for a better theoretical understanding of these problems has become mo...
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Deep learning has received much attention lately due to the impressive empirical performance achieved by training algorithms. Consequently, a need for a better theoretical understanding of these problems has become more evident and multiple works in recent years have focused on this task. In this work, using a unified framework, we show that there exists a polyhedron that simultaneously encodes, in its facial structure, all possible deep neural network training problems that can arise from a given architecture, activation functions, loss function, and sample size. Notably, the size of the polyhedral representation depends only linearly on the sample size, and a better dependency on several other network parameters is unlikely. Using this general result, we compute the size of the polyhedral encoding for commonly used neural network architectures. Our results provide a new perspective on training problems through the lens of polyhedral theory and reveal strong structure arising from these problems. & COPY;2023 Elsevier B.V. All rights reserved.
The neutrosophic mathematical linear programming in its duality fashion is originally exhibited in this manuscript. In accordance with this concept, the relationship of the duality between the neutrosophic objective f...
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Land use configuration in any given landscape is the result of a multi-objective optimization process, which takes into account different ecological, economic, and social factors. In this process, coordinating stakeho...
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Land use configuration in any given landscape is the result of a multi-objective optimization process, which takes into account different ecological, economic, and social factors. In this process, coordinating stakeholders is a key factor to successful spatial land use optimization. Stakeholders need to be modeled as players who have the ability to interact with each other towards their best solution, while considering multiple goals and constraints at the same time. Game theory provides a tool for land use planners to model and analyze such interactions. In order to apply the spatial allocation model and address stakeholder conflicts, an integrated model based on linear programming and game theory was designed in this study. For implementing such model, we conducted an optimal land use allocation process through multi-objective land allocation (MOLA) and linear programming methods. Then, two groups of environmental and land development players were considered to implement the optimization model. The game algorithm was used to select the appropriate constraint so that the result would be acceptable to all stakeholders. The results showed that during the third round of the game, the decision-making process and the optimization of land uses reached the desired Nash Equilibrium state and the conflict between stakeholders was resolved. Ultimately, in order to localize the results, a suitable solution was presented in a GIS environment.
This paper presents the impact of uncoordinated and coordinated charging management of electric vehicles (EVs) on the loading capability of major distribution system equipment, voltage quality, and energy loss in a di...
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This paper presents the impact of uncoordinated and coordinated charging management of electric vehicles (EVs) on the loading capability of major distribution system equipment, voltage quality, and energy loss in a distribution system. The main emphasis is given to the overloading of distribution transformers, primary feeders, and a substation transformer. The voltage quality of load points along the feeders and the system energy loss are also underlined. The load profile for uncoordinated EV charging is simulated by a Monte Carlo method with several deterministic and stochastic variables involved. To mitigate the overloading of the system components, a coordinated charging (also known as smart charging) model formulated as a linear programming problem is proposed with the objective of maximizing the total amount of energy consumption by EVs and the sum of all individual final states of charge (SoCs), and minimizing the sum of the absolute deviation of individual SoCs from the overall average SoC. The optimization problem is subject to equipment capability loading and planning criteria constraints with low, medium, and high EV penetration levels. The voltage quality problem and energy loss are also analyzed by an unbalanced three-phased power flow model. A case study of a real and practical 115/22 kV distribution system of the Provincial Electricity Authority (PEA) with a 50 MVA substation transformer, 5 feeders, and 732 distribution transformers shows that the possibility of overloaded system components, voltage drops along the feeders, and the system energy loss can be identified in the uncoordinated charging scenario and offer the readiness for equipment replacement and network reinforcement planning. The proposed smart charging model allows the distribution system to accommodate more EVs by appropriately managing the power and the start times of charging for the individual EVs over the timeslots of a day. The study results confirm no violation of the system comp
Given two stable matchings in a many-to-one matching market with q-responsive preferences, by manipulating the objective function of the linear program that characterizes the stable matching set, we compute the least ...
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Given two stable matchings in a many-to-one matching market with q-responsive preferences, by manipulating the objective function of the linear program that characterizes the stable matching set, we compute the least upper bound and greatest lower bound between them.
If excess generation caused by increasing of photovoltaic and wind power generation plants is foreseen in a power system, the generation outputs of those plants are curtailed as a last resort in order to maintain the ...
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Background: Lack of dietary diversity in complementary feeding contributes to nutrient gaps leading to undernutrition. Food-based strategies have been successfully used to enrich the complementary diets of infants and...
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Background: Lack of dietary diversity in complementary feeding contributes to nutrient gaps leading to undernutrition. Food-based strategies have been successfully used to enrich the complementary diets of infants and young children. However, context-specific recommendations based on an objective diet optimization is needed to formulate sound and practical nutritional guidelines. Objectives: The present study aimed to identify problem nutrients in complementary diets and formulate complementary feeding recommendations (CFRs) using linear programming analysis for children aged 6 to 23 months in the rural Philippines. Methods: A cross-sectional survey was conducted in the municipality of Mercedes, Philippines. Dietary intakes of breastfed children 6 to 8, 9 to 11, and 12 to 23 months of age (n = 297) were assessed using a multipass 24-hour recall method with 7-day food consumption frequency. A linear programming tool was used to identify the recommended nutrient intakes that could not be met within the existing local food patterns and develop CFRs that would best fulfil nutrient adequacy for 11 modelled micronutrients. Results: Problem nutrients in the current diets were iron and calcium in any age-group, zinc for 6 to 8 and 9 to 11 months old, and thiamine and folate for 12 to 23 months old children. Adoption of CFRs with 4 to 5 food groups in the diet would ensure the adequacy of 7 to 8 nutrients, depending on the age-group. Conclusion: Within the boundaries of local dietary patterns, adequacy for most nutrients could be achieved by promoting realistic servings of nutrient-dense foods and food groups. The linear programming results provide an evidence-based strategy in designing interventions to improve the quality of Filipino complementary diets.
A single-valued neutrosophic set, an generalization of intuitionistic fuzzy set, is a powerful model to deal with uncertainty. In this study we present a method to solve LR-type single-valued neutrosophic linear progr...
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