bankruptcy problem

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Bankruptcy Solutions PROP,CEA,CEL,Talmud-Method in MATLAB Development
This package includes four algorithms for solving bankruptcy problems: 1. Proportional solution (PROP = prop(E, c)) 2. Constrained equal award solution (CEA = cea(E, c)) 3. Constrained equivalent loss solution (CEL = cel(E, c)) 4. Talmud solution (TAL = talmud(E, c)) Additionally, it contains a func
Weber Problem Solver Generalization of Weiszfeld Algorithm in MATLAB
在几何学中,以阿尔弗雷德·韦伯命名的韦伯问题是位置理论中最著名的问题之一。它需要在平面上找到一个点,该点使从该点到n个目的地点的运输成本总和最小,其中不同的目的地点与不同的单位距离成本相关联。
Fixed-Point Multiple Traveling Salesman Problem with Genetic Algorithm in MATLAB
固定起点/终点多旅行推销员问题 (M-TSP) 通过遗传算法 (GA) 解决 MTSPF_GA 是一个用于解决 固定多重旅行商问题(M-TSP)的 遗传算法(GA),其目的是通过GA搜索找到接近最优解的最短路线。每位推销员都从起点出发,经过一组独特的城市,最终返回起点。 主要特点: 每个推销员从第一个点出发,到第一个点结束,但旅行到中间的一组独特城市。 除了第一个城市,其他每个城市仅被一位推销员访问。 注意: 固定起点/终点位置被视为第一个XY点。 输入参数: XY(float):一个Nx2的城市位置矩阵,其中N为城市数量。 DMAT(float):城市间距离或成本的NxN矩阵。 NSA
TimeTabling-GeneticAlgorithm Genetic Algorithm Solution for Weekly Timetable Problem in MATLAB
遗传算法是为无法通过称为NP-Hard问题的标准方法解决的问题找到足够好的解决方案的方法。虽然它不能保证最好的解决方案,但我们可以在该方法中为大多数工程问题找到相对足够好的解决方案[1]。高中大学等教育机构使用每周课程时间表以最佳方式使用所有资源。制定最佳每周时间表就是NP-Hard问题的一个例子,它无法用任何检查每个概率的粗暴方法解决。在这个存储库中,我们使用遗传算法提供了该问题的解决方案,该算法试图最小化确定的适应度函数,该函数是对时间表如何优化的一种度量[2]。
Wrox.Microsoft.SQL.Server.2008.Integration.Services.Problem.Design.Solution
Wrox.Microsoft.SQL.Server.2008.Integration.Services.Problem.Design.Solution提供了SQL Server 2008集成服务的全面指南,涵盖了问题设计和解决方案的详细步骤。该书详细介绍了如何有效地设计和实施SQL Server 2008集成服务解决方案,包括数据流、控制流、错误处理和日志记录。通过实际案例和最佳实践,读者能够学习如何优化数据集成和处理流程,以满足各种复杂业务需求。
978-1-4842-0560-0_MATLAB_Recipes_Problem_Solution_Approach.pdf
MATLAB Recipes: A Problem-Solution Approach Michael Paluszek, Stephanie Thomas Princeton, New Jersey, USA Princeton Junction, New Jersey, USA ISBN-13 (pbk): 978-1-4842-0560-0ISBN-13 (electronic): 978-1-4842-0559-4DOI: 10.1007/978-1-4842-0559-4Library of Congress Control Number: 2015955885 Copyright
Entropy Method MATLAB Code for Distribution Planning FSC Decomposition-Based Solver for FSC Problem
The Conservative Value Method MATLAB code Distribution_Planning_Lot_sizing_Decomposition.m is used for the Lagrangian Relaxation Method and decomposition algorithms applied to high-speed railway (CSHR) catering services. These programs are coded based on the following works: the time-varying demand
deconvtv-Fast Algorithm for Total Variation Deconvolution A Numerical Solver for Total Variation Regularized Least Squares Deconvolution Problem in MATLAB
Total variation regularized least squares deconvolution is one of the standard problems in image processing. This package uses the concept of Augmented Lagrangian [1] to implement the state-of-the-art algorithm, which can be viewed as a variant of the widely known Alternating Direction Method of Mul
Differential Scheme for Solving Problem 7A Dynamic Scripting Approach in Java-based Groovy Programming(2nd Edition)
The following differential schemes are used to solve the given problem: First Scheme: Combining equations (18), (21), and (22), we derive a differential scheme for solving problem (7). The general form is given as follows:[u^{n+1} = u^n + \Delta t \left( -\left( \frac{d^2 u}{dx^2} \right)^n \right
Energy Control Problem Code in MATLAB-GCNMF-s2k Group Constrained Non-negative Matrix Factorization with Sum-k Constraint for Load Disaggregation
Energy Control Problem Code in MATLAB: Non-Intrusive Load Monitoring (NILM) for HVAC Systems This repository contains the dataset we collected for HVAC energy disaggregation, as well as the source code and demonstrations from our paper in IEEE Transactions on Power Systems. To the best of our knowle