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Journal articles on the topic 'Dual-simplex'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Safitri, Elfira, Sri Basriati, and Elvina Andiani. "PENERAPAN PROGRAM LINIER MENGGUNAKAN METODE DUAL SIMPLEKS DAN METODE QUICK SIMPLEKS UNTUK MEMINIMUMKAN BIAYA (STUDI KASUS: KELOMPOK WANITA TANI (KWT) SENTOSA SANTUL)." Journal of Fundamental Mathematics and Applications (JFMA) 4, no. 1 (2021): 117–32. http://dx.doi.org/10.14710/jfma.v4i1.8879.

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The Sentosa Santul Women Farmers Group (KWT) is a group of women farmers in Dusun Santul, Kampar Utara District an is engaged in the field of food crops is chili. The Sentosa Santul Women Farmers group (KWT) uses 4 types of fertilizers for chili plant fertilization, namely hydro complex fertilizer, phonska, NPK Zamrud and goat manure.The KWT wants the minimum fertilizer cost but the nutrients in the plants are met. The method used in this research is the dual simplex method and the quick simplex method. The purpose of this study is to determine the minimum costs that must be incurred by the Wo

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2

Geranis, George, Konstantinos Paparizzos, and Angelo Sifaleras. "A dual exterior point simplex type algorithm for the minimum cost network flow problem." Yugoslav Journal of Operations Research 19, no. 1 (2009): 157–70. http://dx.doi.org/10.2298/yjor0901157g.

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A new dual simplex type algorithm for the Minimum Cost Network Flow Problem (MCNFP) is presented. The proposed algorithm belongs to a special 'exterior- point simplex type' category. Similarly to the classical network dual simplex algorithm (NDSA), this algorithm starts with a dual feasible tree-solution and reduces the primal infeasibility, iteration by iteration. However, contrary to the NDSA, the new algorithm does not always maintain a dual feasible solution. Instead, the new algorithm might reach a basic point (tree-solution) outside the dual feasible area (exterior point - dual infeasibl

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3

Abdolali, Maryam, Giovanni Barbarino, and Nicolas Gillis. "Dual Simplex Volume Maximization for Simplex-Structured Matrix Factorization." SIAM Journal on Imaging Sciences 17, no. 4 (2024): 2362–91. https://doi.org/10.1137/24m1650600.

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4

Samaras, Nikolaos, Angelo Sifelaras, and Charalampos Triantafyllidis. "A primal-dual exterior point algorithm for linear programming problems." Yugoslav Journal of Operations Research 19, no. 1 (2009): 123–32. http://dx.doi.org/10.2298/yjor0901123s.

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The aim of this paper is to present a new simplex type algorithm for the Linear Programming Problem. The Primal - Dual method is a Simplex - type pivoting algorithm that generates two paths in order to converge to the optimal solution. The first path is primal feasible while the second one is dual feasible for the original problem. Specifically, we use a three-phase-implementation. The first two phases construct the required primal and dual feasible solutions, using the Primal Simplex algorithm. Finally, in the third phase the Primal - Dual algorithm is applied. Moreover, a computational study

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5

Bixby, Robert E., and Alexander Martin. "Parallelizing the Dual Simplex Method." INFORMS Journal on Computing 12, no. 1 (2000): 45–56. http://dx.doi.org/10.1287/ijoc.12.1.45.11902.

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6

Orlin, James B., Serge A. Plotkin, and Éva Tardos. "Polynomial dual network simplex algorithms." Mathematical Programming 60, no. 1-3 (1993): 255–76. http://dx.doi.org/10.1007/bf01580615.

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7

Sousa, Ricardo Silveira, Carla Taviane Lucke da Silva, and Marcos Nereu Arenales. "Métodos do tipo dual simplex para problemas de otimização linear canalizados." Pesquisa Operacional 25, no. 3 (2005): 349–82. http://dx.doi.org/10.1590/s0101-74382005000300004.

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Neste artigo estudamos o problema de otimização linear canalizado (restrições e variáveis canalizadas, chamado formato geral) e desenvolvemos métodos do tipo dual simplex explorando o problema dual, o qual é linear por partes, num certo sentido não-linear. Várias alternativas de busca unidimensional foram examinadas. Experimentos computacionais revelam que a busca unidimensional exata na direção dual simplex apresenta melhor desempenho.

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8

Nasseri, Seyed Hadi, and Ali Ebrahimnejad. "Sensitivity Analysis on Linear Programming Problems with Trapezoidal Fuzzy Variables." International Journal of Operations Research and Information Systems 2, no. 2 (2011): 22–39. http://dx.doi.org/10.4018/joris.2011040102.

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In the real word, there are many problems which have linear programming models and sometimes it is necessary to formulate these models with parameters of uncertainty. Many numbers from these problems are linear programming problems with fuzzy variables. Some authors considered these problems and have developed various methods for solving these problems. Recently, Mahdavi-Amiri and Nasseri (2007) considered linear programming problems with trapezoidal fuzzy data and/or variables and stated a fuzzy simplex algorithm to solve these problems. Moreover, they developed the duality results in fuzzy e

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9

Klabjan, Diego, Ellis L. Johnson, and George L. Nemhauser. "A parallel primal–dual simplex algorithm." Operations Research Letters 27, no. 2 (2000): 47–55. http://dx.doi.org/10.1016/s0167-6377(00)00017-1.

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10

Matsumoto, J., and L. W. Mays. "Dual simplex method for GUB problems." Journal of Optimization Theory and Applications 45, no. 1 (1985): 113–22. http://dx.doi.org/10.1007/bf00940817.

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11

Huangfu, Q., and J. A. J. Hall. "Parallelizing the dual revised simplex method." Mathematical Programming Computation 10, no. 1 (2017): 119–42. http://dx.doi.org/10.1007/s12532-017-0130-5.

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12

Shim, Sangho, Ellis L. Johnson, and Wenwei Cao. "Primal-dual simplex method for shooting." Electronic Notes in Discrete Mathematics 36 (August 2010): 719–26. http://dx.doi.org/10.1016/j.endm.2010.05.091.

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13

Badr, Elsayed, and Sultan Almotairi. "On a Dual Direct Cosine Simplex Type Algorithm and Its Computational Behavior." Mathematical Problems in Engineering 2020 (May 11, 2020): 1–8. http://dx.doi.org/10.1155/2020/7361092.

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The goal of this paper is to propose a dual version of the direct cosine simplex algorithm (DDCA) for general linear problems. The proposed method has not artificial variables, so it is different from both the two-phase method and big-M method. Our technique solves the dual Klee–Minty problem via two iterations and solves the dual Clausen problem via four iterations. The power of the proposed algorithm is evident from the extensive experimental results on benchmark problems adapted from NETLIB. Preliminary results indicate that this dual direct cosine simplex algorithm (DDCA) reduces the numbe

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14

Cheung, Wing-Sum, and Ge Xiong. "CHORD POWER INTEGRALS OF SIMPLICES." Asian-European Journal of Mathematics 02, no. 04 (2009): 557–65. http://dx.doi.org/10.1142/s1793557109000479.

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In this paper, we obtain a formula relating the chord power integrals of a simplex K and the dual quermassintegrals of its difference body DK. As interesting applications, we express the volumes of difference body DK and polar projection body Π*K in terms of the volume of simplex K. Santaló-type inequality for chord power integrals of simplex is also established.

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15

Voulgaropoulou, Sophia, Nikolaos Samaras, and Nikolaos Ploskas. "Predicting the Execution Time of the Primal and Dual Simplex Algorithms Using Artificial Neural Networks." Mathematics 10, no. 7 (2022): 1038. http://dx.doi.org/10.3390/math10071038.

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Selection of the most efficient algorithm for a given set of linear programming problems has been a significant and, at the same time, challenging process for linear programming solvers. The most widely used linear programming algorithms are the primal simplex algorithm, the dual simplex algorithm, and the interior point method. Interested in algorithm selection processes in modern mathematical solvers, we had previously worked on using artificial neural networks to formulate and propose a regression model for the prediction of the execution time of the interior point method on a set of benchm

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16

Srinivas, Martha. "A Key Note on Dual Simplex Method." International Journal of Mathematics Trends and Technology 64, no. 2 (2018): 72–73. http://dx.doi.org/10.14445/22315373/ijmtt-v64p511.

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17

Maros, István. "A generalized dual phase-2 simplex algorithm." European Journal of Operational Research 149, no. 1 (2003): 1–16. http://dx.doi.org/10.1016/s0377-2217(02)00448-4.

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18

Paparrizos, Konstantinos, Nikolaos Samaras, and George Stephanides. "A new efficient primal dual simplex algorithm." Computers & Operations Research 30, no. 9 (2003): 1383–99. http://dx.doi.org/10.1016/s0305-0548(02)00077-1.

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19

Vaidya, N. "Application of Quick Simplex Method on the Dual Simplex Method (A New Approach)." Journal of Advances in Mathematics and Computer Science 24, no. 5 (2017): 1–9. http://dx.doi.org/10.9734/jamcs/2017/36357.

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20

WANG, PEI-ZHUANG. "CONE-CUTTING: A VARIANT REPRESENTATION OF PIVOT IN SIMPLEX." International Journal of Information Technology & Decision Making 10, no. 01 (2011): 65–82. http://dx.doi.org/10.1142/s0219622011004221.

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This study presents a variant representation of pivot in simplex, which performs cone-cutting on a cone C in dual space to match the pivot performed on a basis B, while the edge-vectors of C are indicated by the row vectors of the feature matrix F = B-1 in the simplex table. Under this representation, we can see the dual cone C of basis B through the feature matrix F directly, and we can perform pivot motivated by the monitor viewing toward the dual space. As an example, a constraint plane in the dual space is delete-able for the optimal searching if it does not pass through the dual optimal p

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21

صالح, سرمد علوان. "إيجاد الحل المقبول (الممكن) والأمثل لأنموذج البرمجة الخطية في ظل عدم تحقق شرطّي الإمكانية والأمثلية". Journal of Economics and Administrative Sciences 14, № 52 (2008): 257. http://dx.doi.org/10.33095/jeas.v14i52.1428.

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Consider the Linear Programming (LP) active & effective factor in decision maker & taker process . So that given certain goals , the Significance of (LP) in solving & evaluation the activity during one tools (General Simplex Mehtod)that the solution is Feasible &no optimal then called (Primal Simplex Method) or vice-versa then called(Dual Simplex Method).Same of cases the solution is infeasible & no optimal then using the two methods alternatively once to find the feasible solution and other to find optimal solution   

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22

Guder, Faruk, and Francis J. Nourie. "A Dual Simplex Algorithm for Piecewise-Linear Programming." Journal of the Operational Research Society 47, no. 4 (1996): 583. http://dx.doi.org/10.2307/3010733.

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23

Güder, Faruk, and Francis J. Nourie. "A Dual Simplex Algorithm for Piecewise-Linear Programming." Journal of the Operational Research Society 47, no. 4 (1996): 583–90. http://dx.doi.org/10.1057/jors.1996.63.

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24

Mahapatra, Nirmal Kumar, and Tuhin Bera. "Optimisation by dual simplex approach in neutrosophic environment." International Journal of Fuzzy Computation and Modelling 2, no. 4 (2019): 334. http://dx.doi.org/10.1504/ijfcm.2019.10022113.

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25

Bera, Tuhin, and Nirmal Kumar Mahapatra. "Optimisation by dual simplex approach in neutrosophic environment." International Journal of Fuzzy Computation and Modelling 2, no. 4 (2019): 334. http://dx.doi.org/10.1504/ijfcm.2019.100347.

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26

Pan, Ping-Qi. "A dual projective simplex method for linear programming." Computers & Mathematics with Applications 35, no. 6 (1998): 119–35. http://dx.doi.org/10.1016/s0898-1221(98)00024-8.

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27

Ehrgott, M., J. Puerto, and A. M. Rodríguez-Chía. "Primal-Dual Simplex Method for Multiobjective Linear Programming." Journal of Optimization Theory and Applications 134, no. 3 (2007): 483–97. http://dx.doi.org/10.1007/s10957-007-9232-y.

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28

Curet, Norman D. "A primal-dual simplex method for linear programs." Operations Research Letters 13, no. 4 (1993): 233–37. http://dx.doi.org/10.1016/0167-6377(93)90045-i.

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29

Goldfarb, D. "Efficient dual simplex algorithms for the assignment problem." Mathematical Programming 34, no. 3 (1986): 372. http://dx.doi.org/10.1007/bf01582238.

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30

Goldfarb, D. "Efficient dual simplex algorithms for the assignment problem." Mathematical Programming 33, no. 2 (1985): 187–203. http://dx.doi.org/10.1007/bf01582245.

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31

Armstrong, Ronald D., and Zhiying Jin. "A new strongly polynomial dual network simplex algorithm." Mathematical Programming 78, no. 2 (1997): 131–48. http://dx.doi.org/10.1007/bf02614366.

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32

Hough, C. L., and Y. Chang. "Constrained Cutting Rate-Tool Life Characteristic Curve, Part 2: Convex Programs." Journal of Manufacturing Science and Engineering 120, no. 1 (1998): 160–65. http://dx.doi.org/10.1115/1.2830093.

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Based on the concept in Part 1, Theory and General Case, algorithms to determine the constrained R-T characteristic curve are established for convex constrained machining economics problems. The first algorithm is for posynomial problems with the linear-logarithmic tool life equation. The R-T curve may be determined by applying the simplex method to the log-dual problems. Sensitivity analysis of the optimal simplex tableau enables obtaining the loci of optima easily. The second algorithm is for the quadratic posylognomial problems with quadratic-logarithmic tool life equation using the propert

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33

Visuthirattanamanee, Rujira, Krung Sinapiromsaran, and Aua-aree Boonperm. "Self-Regulating Artificial-Free Linear Programming Solver Using a Jump and Simplex Method." Mathematics 8, no. 3 (2020): 356. http://dx.doi.org/10.3390/math8030356.

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An enthusiastic artificial-free linear programming method based on a sequence of jumps and the simplex method is proposed in this paper. It performs in three phases. Starting with phase 1, it guarantees the existence of a feasible point by relaxing all non-acute constraints. With this initial starting feasible point, in phase 2, it sequentially jumps to the improved objective feasible points. The last phase reinstates the rest of the non-acute constraints and uses the dual simplex method to find the optimal point. The computation results show that this method is more efficient than the standar

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34

Jojic, Dusko. "Extendable shelling, simplicial and toric h-vector of some polytopes." Publications de l'Institut Math?matique (Belgrade), no. 95 (2007): 85–93. http://dx.doi.org/10.2298/pim0795085j.

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We show that the stellar subdivisions of a simplex are extendably shellable. These polytopes appear as the facets of the dual of a hypersimplex. Using this fact, we calculate the simplicial and toric h-vector of the dual of a hypersimplex. Finally, we calculate the contribution of each shelling component to the toric h-vector.

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35

Whallett, Elizabeth J., and Ahmes L. Pahor. "Herpes and the head and neck: the difficulties in diagnosis." Journal of Laryngology & Otology 113, no. 6 (1999): 573–77. http://dx.doi.org/10.1017/s0022215100144524.

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AbstractA case of primary herpes of the head and neck is presented. The exact source of infection and the precise diagnosis proved difficult to establish, but evidence tended to support a diagnosis of varicella zoster infection as opposed to a herpes simplex infection, though a dual infection was not ruled out.Herpes simplex has specific clinical features which usually make its distinction from varicella zoster clear cut. In this case we relied heavily on laboratory investigations to improve the accuracy of our diagnosis since the clinical characteristics were blurred.Unlike varicella zoster t

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36

KITAHARA, TOMONARI, and SHINJI MIZUNO. "AN UPPER BOUND FOR THE NUMBER OF DIFFERENT SOLUTIONS GENERATED BY THE PRIMAL SIMPLEX METHOD WITH ANY SELECTION RULE OF ENTERING VARIABLES." Asia-Pacific Journal of Operational Research 30, no. 03 (2013): 1340012. http://dx.doi.org/10.1142/s0217595913400125.

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Recently, Kitahara, and Mizuno derived an upper bound for the number of different solutions generated by the primal simplex method with Dantzig's (the most negative) pivoting rule. In this paper, we obtain an upper bound with any pivoting rule which chooses an entering variable whose reduced cost is negative at each iteration. The upper bound is applied to a linear programming problem with a totally unimodular matrix. We also obtain a similar upper bound for the dual simplex method.

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37

Samarin, Victor I. "Composite Principal-Dual Simplex Method for Linear Programming Solving." Modeling of Artificial Intelligence 3, no. 3 (2014): 126–32. http://dx.doi.org/10.13187/mai.2014.3.126.

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38

Hu, Jing, and Ellis L. Johnson. "Computational results with a primal–dual subproblem simplex method." Operations Research Letters 25, no. 4 (1999): 149–57. http://dx.doi.org/10.1016/s0167-6377(99)00048-6.

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39

FRIEDMAN, H. "Keratin, a dual role in herpes simplex virus pathogenesis." Journal of Clinical Virology 35, no. 1 (2006): 103–5. http://dx.doi.org/10.1016/j.jcv.2005.03.008.

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40

Balinski, M. L. "A competitive (dual) simplex method for the assignment problem." Mathematical Programming 34, no. 2 (1986): 125–41. http://dx.doi.org/10.1007/bf01580579.

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41

Omer, Jérémy, Mehdi Towhidi, and François Soumis. "The positive edge pricing rule for the dual simplex." Computers & Operations Research 61 (September 2015): 135–42. http://dx.doi.org/10.1016/j.cor.2015.03.009.

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42

Jdid, Maissam, and Florentin Smarandache. "Neutrosophic Treatment of Duality Linear Models and the Binary Simplex Algorithm." Prospects for Applied Mathematics and Data Analysis 2, no. 2 (2023): 08–21. http://dx.doi.org/10.54216/pamda.020202.

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One of the most important theories in linear programming is the dualistic theory and its basic idea is that for every linear model has dual linear model, so that solving the original linear model gives a solution to the dual model. Therefore, when we solving the linear programming model, we actually obtain solutions for two linear models. In this research, we present a study of the models. The neutrosophic dual and the binary simplex algorithm, which works to find the optimal solution for the original and dual models at the same time. The importance of this algorithm is evident in that it is r

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43

MOHAN, S. R., S. K. NEOGY, and T. PARTHASARATHY. "PIVOTING ALGORITHMS FOR SOME CLASSES OF STOCHASTIC GAMES: A SURVEY." International Game Theory Review 03, no. 02n03 (2001): 253–81. http://dx.doi.org/10.1142/s0219198901000385.

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In this paper, we survey the recent literature on computing the value vector and the associated optimal strategies of the players for special cases of zero-sum stochastic games, or in computing a Nash equilibrium point and the corresponding stationary strategies of the players for special cases of nonzero-sum stochastic games, using finite-step algorithms based on pivoting. Examples of finite-step pivoting algorithms are the various simplex-type algorithms, such as the primal simplex or dual simplex method for solving the linear programming problem or Lemke's or Lemke-Howson's algorithm for so

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44

Darvishi Salookolaei, Davood, and Seyed Hadi Nasseri. "A dual simplex method for grey linear programming problems based on duality results." Grey Systems: Theory and Application 10, no. 2 (2020): 145–57. http://dx.doi.org/10.1108/gs-10-2019-0044.

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PurposeFor extending the common definitions and concepts of grey system theory to the optimization subject, a dual problem is proposed for the primal grey linear programming problem.Design/methodology/approachThe authors discuss the solution concepts of primal and dual of grey linear programming problems without converting them to classical linear programming problems. A numerical example is provided to illustrate the theory developed.FindingsBy using arithmetic operations between interval grey numbers, the authors prove the complementary slackness theorem for grey linear programming problem a

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45

Fu, Chao, Guojin Feng, Jiaojiao Ma, Kuan Lu, Yongfeng Yang, and Fengshou Gu. "Predicting the Dynamic Response of Dual-Rotor System Subject to Interval Parametric Uncertainties Based on the Non-Intrusive Metamodel." Mathematics 8, no. 5 (2020): 736. http://dx.doi.org/10.3390/math8050736.

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In this paper, the non-probabilistic steady-state dynamics of a dual-rotor system with parametric uncertainties under two-frequency excitations are investigated using the non-intrusive simplex form mathematical metamodel. The Lagrangian formulation is employed to derive the equations of motion (EOM) of the system. The simplex form metamodel without the distribution functions of the interval uncertainties is formulated in a non-intrusive way. In the multi-uncertain cases, strategies aimed at reducing the computational cost are incorporated. In numerical simulations for different interval parame

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46

Azeez, Halgurd N., and Abdulqader O. Ameen. "SOLVING STOCHASTIC TRANSPORTATION ELECTRICITY PROBLEM WITH FUZZY INFORMATION ON PROBABILITY DISTRIBUTION USING MATLAB PROGRAM." Science Journal of University of Zakho 12, no. 1 (2024): 116–37. http://dx.doi.org/10.25271/sjuoz.2024.12.1.1212.

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This study focuses on MATLAB code programs of the entire stages of solving Stochastic Transportation Linear Programming Problems with Fuzzy Uncertainty Information on Probability Distribution Space (STLPPFI) with its algorithm outlines. A MATLAB code program of STLPPFI problem solver with algorithm outlines are proposed to solve STLPPFI model problems, and it utilizes many concepts as Alpha-Cut technique, Truth Degrees technique, Linear Fuzzy Membership Function (LFMF), Trapezoidal Fuzzy Number , Triangular Fuzzy Number , Linear Fuzzy Ranking Function (LFRF), Expectation Weighted Summation tec

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47

Sangeetha, V., K. Thirisangu, and P. Elumalai. "Dual Simplex Method Based solution for a Fuzzy Transportation Problem." Journal of Physics: Conference Series 1947, no. 1 (2021): 012017. http://dx.doi.org/10.1088/1742-6596/1947/1/012017.

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48

Tamura, Akihisa, Hitoshi Takehara, Komei Fukuda, Satoru Fujishige, and Masakazu Kojima. "A DUAL INTERIOR PRIMAL SIMPLEX METHOD FOR LINEAR PROGRAMMING METHOD." Journal of the Operations Research Society of Japan 31, no. 3 (1988): 413–30. http://dx.doi.org/10.15807/jorsj.31.413.

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49

Ogryczak, W. "Dual simplex algorithm with implicit representation of variable upper bounds." Optimization 33, no. 4 (1995): 321–38. http://dx.doi.org/10.1080/02331939508844084.

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50

Akgül, Mustafa. "A sequential dual simplex algorithm for the linear assignment problem." Operations Research Letters 7, no. 3 (1988): 155–58. http://dx.doi.org/10.1016/0167-6377(88)90082-x.

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