The linear programming (LP) approach is, together with value iteration and policy iteration, one of the three fundamental methods to solve optimal control problems in a dynamic programming setting. Despite its simple ...
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We deal with linear programming problems involving absolute values in their formulations, so that they are no more expressible as standard linear programs. The presence of absolute values causes the problems to be non...
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Despite many deterministic approaches for the optimal design of a canal already proposed, a methodology capable of considering the risk value when there is uncertainty in flow estimation is still lacking. In real engi...
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Despite many deterministic approaches for the optimal design of a canal already proposed, a methodology capable of considering the risk value when there is uncertainty in flow estimation is still lacking. In real engineering problems, we confront linear programming models in which all included uncertain parameters are fuzzy numbers. In the task of canal design, this assumption is because it involves uncertain parameters (load and resistance) estimated by short historical data and limited knowledge about the environment, respectively. This limitation hinders the usage of probabilistic linear programming approaches because the probability of satisfying a constraint should be known with certainty. This paper provides a new method for solving fuzzy number linear programming problems using the concept of fuzzy risk and Yager's fuzzy ranking function. The result is used for proposing a novel optimization formula that can aid in rectangular canal design. The application of our insightful new methodology is presented in a stormwater canal design example. The findings presented in this paper will appeal to decision-makers and practicing engineers.
In this paper, we provide an affirmative answer to the long-standing question: Are GPUs useful in solving linear programming? We present ***, a GPU implementation of restarted primal-dual hybrid gradient (PDHG) for so...
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How to solve high-dimensional linear programs (LPs) efficiently is a fundamental question. Recently, there has been a surge of interest in reducing LP sizes using random projections, which can accelerate solving LPs i...
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Sentinel-1 is a synthetic aperture radar platform that provides free and open-source images of the Earth. A product type of Sentinel-1 is ground range detected (GRD), which records intensity while discarding phase inf...
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Sentinel-1 is a synthetic aperture radar platform that provides free and open-source images of the Earth. A product type of Sentinel-1 is ground range detected (GRD), which records intensity while discarding phase information from the radar backscatter. Especially in cross-polarized GRD images, there are noticeable intensity changes throughout the image that are caused by amplifying the noise floor of the signal, which varies due to the nonuniform radiation pattern of the satellite's antenna. While Sentinel-1 has instrument processing facility (IPF) software to estimate the noise floor, even in the newer versions (3.1 or above) of the IPF software there are still instances where the estimates provided do not fit the actual noise floor in the image, which is particularly noticeable in transitions between adjacent subswaths. In this work, we propose a method that reduces the impact of the varying noise-floor throughout the image. The method models the intensity of the noise floor to be a power function of the radiation pattern power. The method divides the swath into several sections depending on the location of the local minimum and maximum of the radiation pattern power with respect to the range. The parameter estimation is portrayed as a geometric programming problem that is transformed into a linear programming problem by logarithmic transformation. Affine offsets are computed for each subswath by a weighted least squares approach. Vast improvement is found on extra-wide (EW) and interferometric wide (IW) Sentinel-1 modes over cross-polarized images. Code implementation is available at https://***/PeterQLee/sentinel1_denoise_rs.
We study the properties of the constructive linear programming problems. The parameters of linear functions in such problems are constructive real numbers. To solve such a problem is to find the optimal plan with the ...
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In the last 10 years, the aeronautical sector has experienced a high impact growth worldwide. This directly affects the growth and development of aeronautical maintenance due to the increase in aircraft purchases. For...
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ISBN:
(纸本)9781450397582
In the last 10 years, the aeronautical sector has experienced a high impact growth worldwide. This directly affects the growth and development of aeronautical maintenance due to the increase in aircraft purchases. For this reason, Certified Repair Stations play an important role in this current high demanded sector. This research aims to increase the efficiency of aircraft maintenance operations in a certified repair station. Currently, the efficiency level is 77.18% and is below 95% recommended for this sector. This negatively affects the economic situation of the company since in the period from 2018 to 2020, 39 work orders were not attended, which represents 14% of the total turnover. For this reason, a resource optimization model has been designed using the Lean Six Sigma methodology under the DMAIC tool, to run the linear programming using Lingo subsequently. After the simulation, efficiency reaches 100%, which is within the range established by aeronautical standards; likewise, delay costs decrease by 100%. Finally, it is expected that the model described above can be applied in certified repair stations with similar problems.
Map coloring is a classic problem in graph theory and it relates to many optimization techniques in mathematics such as linear programming and simulated *** paper investigates the minimum number of colors required to ...
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Map coloring is a classic problem in graph theory and it relates to many optimization techniques in mathematics such as linear programming and simulated *** paper investigates the minimum number of colors required to color a map under different constraints and situations using linear ***,it examines three different scenarios:(1) coloring each district on the map with the constraint that adjacent districts must be colored differently,(2) adding the additional constraint that two regions bordering the same region cannot be colored the same,and(3) assigning two colors to each district with the constraint that adjacent districts must be colored *** proceed with the research,hypotheses are formulated regarding the impact of these additional constraints on the minimum number of colors required to color the *** data in the paper is collected by creating sample maps and analyzing the minimum number of colors required to color them under each of the different *** findings of this research suggest that the addition of constraints,indicating a complex situation,increases the minimum number of colors needed to color the ***,linear programming is found to be an effective optimization technique for solving map coloring problems under these *** research makes a valuable contribution to the field of mathematics and computer science,providing insights into the application of optimization techniques to real-world problems like map *** findings of the research have significant implications for practitioners working in the field of optimization and inform the development of more efficient algorithms for solving map coloring problems.
The main challenge addressed in this paper is to identify individual terms in a superposition of heat kernels on a graph. We establish geometric conditions on the vertices at which these heat kernels are centered and ...
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