Anwaar Hazoor Ansari · Journal of Applied Mathematics and Physics · 2019
The purpose of this research paper is to introduce Easy Simplex Algorithm which is developed by author. The simplex algorithm first presented by G. B. Dantzing, is generally used for solving a Linear programming problem (LPP). One of the important steps of the simplex algorithm is to convert all unequal constraints into equal form by adding slack variables then proceeds to basic solution. Our new algorithm i) solves the LPP without equalize the constraints and ii) leads to optimal solution definitely in lesser time. The goal of suggested algorithm is to improve the simplex algorithm so that the time of solving an LPP will be definitely lesser than the simplex algorithm. According to this Easy Simplex (AHA Simplex) Algorithm the use of Big M method is not required.
Cited by 3Open access
Andrea Carpignani, M. Pappalardo · Unitext · 2026
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2013
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SpringerReference · 2011
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Siriphong Lawphongpanich · Encyclopedia of Optimization · 2008
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Glenn Hurlbert · Undergraduate texts in mathematics · 2009
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Jose Mathew Manimala · arXiv (Cornell University) · 2010
The evolution of encryption algorithms have led to the development of very complicated and highly versatile algorithms that sacrifice efficiency for better and harder to decrypt results. But by the application of a genetic schema to the encryption of data, a new structure can be created. Genetic methods and procedures are lethal in the way they handle and manipulate data. The RAmM algorithm uses four genetic operations that have been developed specifically for encryption of data. The operations are Replication, Augmentation, Mutation and Multiplication. The proper application of these methods according to the rules that have been found to be the best for getting optimal and correct results produces a "fingerprint" that is unique to a pair of . This means that every single data entry can only be decrypted by using the correct set of key. The application of the RAmM algorithm is in the field of image encryption and restoration. The boundary and the pixel values are separately encrypted to produce a very genuine sequence that is never understood to be an image. The beauty of the procedure is that the entire image can be reproduced without any color loss or loss of pixel quality.
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Xavier Allamigeon, Pascal Benchimol, Stéphane Gaubert et al. · arXiv (Cornell University) · 2013
We develop a tropical analog of the simplex algorithm for linear programming. In particular, we obtain a combinatorial algorithm to perform one tropical pivoting step, including the computation of reduced costs, in O(n(m+n)) time, where m is the number of constraints and n is the dimension.
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Νικόλαος Πλόσκας, Nikolaos Samaras · Springer optimization and its applications · 2017
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WORLD SCIENTIFIC eBooks · 2024
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Moncayo-Martínez, Luis A · 2021
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Xavier Allamigeon, Pascal Benchimol, Stéphane Gaubert et al. · SIAM Journal on Discrete Mathematics · 2015
We develop a tropical analogue of the simplex algorithm for linear programming. In particular, we obtain a combinatorial algorithm to perform one tropical pivoting step, including the computation of reduced costs, in $O(n(m+n))$ time, where $m$ is the number of constraints and $n$ is the dimension.
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Quirino Paris · Palgrave Macmillan US eBooks · 2016
In chapter 7 we studied the primal simplex algorithm which, for several years after its discovery, was regarded as a procedure to find a LP solution working on the primal problem. Analogously, a procedure that solves a dual linear programming problem may be called a dual simplex algorithm. This algorithm was discovered by C. E. Lemke in 1954, seven years after the primal simplex procedure. It is fair to say that without the dual simplex algorithm modern computer codes could not be as reliable as they are. At present, any respectable computer program based on the simplex method incorporates both the primal and the dual simplex algorithms. The reason for the importance of the dual simplex algorithm has its source in the duality and symmetry of linear programming. That it took seven years to discover it is somewhat of a mystery given the obvious symmetry of linear programming.KeywordsDual ProblemPrimal ProblemDual SolutionSimplex AlgorithmPrimal SolutionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Νικόλαος Πλόσκας, Nikolaos Samaras · Springer optimization and its applications · 2017
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David Evans, Graham M. Megson · International Journal of Computer Mathematics · 1991
In this paper a systolic algorithm is presented for the Simplex algorithm as used in Linear Programming applications. In addition, to reduce computer storage requirements, a revised form of the algorithm is considered for systolic array implementation using the product form of the inverse.
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Richard W. Weber · Princeton University Press eBooks · 2010
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JOAQUIM PEDRO DE V CORDEIRO · 2008
Este trabalho busca desenvolver o método Simplex para \nRedes na solução de\nproblemas de Fluxo de Custo Mínimo. Este método consiste \nem uma adaptação do\nmétodo Simplex primal em que são exploradas as \ncaracterísticas específicas da rede\nsubjacente ao problema ao se buscar a solução ótima em um \nnúmero finito de árvores\ngeradoras. A árvore geradora ótima será obtida \niterativamente através de sucessivas\nmelhorias na estrutura de cada árvore formada. A maior \neficiência do Simplex para Redes\nse dá tanto no menor número de iterações necessárias para \nse atingir o ótimo, quanto na\nmaior velocidade destas iterações, trata-se, portanto, de \num método bastante poderoso na\nresolução de problemas de Fluxo de Custo Mínimo. Serão, \ntambém, abordados aspectos\npráticos da implementação do algoritmo além da aplicação \ndeste algoritmo implementado\nem VBA (Visual Basic for Applications) em um problema \nprático a título de\nexemplificação.
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2015
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Mohit Mahajan, Rakesh Nagi · Journal of Parallel and Distributed Computing · 2023
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Karel Ouzký · Digital Repository (National Repository of Grey Literature) · 2009
Basic idea of fractal simplex algorithm is based in the theory of matrix counting and knowledge of matrix representation of simplex tabuleao from revised simplex method. My desire is to explain theoretical basics on which this algorithm works and provide solution in language Visual Basic for Applications in application MS Excel 2007. Main benefit I see in the fact, that algorithm can solved specific class of mathematical problems in a way of exactness counting whithout necessity of using decimal numbers.
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