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Artículos de revistas sobre el tema "Integer programming"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 30 de julio de 2024

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1

Wampler, Joe F. y Stephen E. Newman. "Integer Programming". College Mathematics Journal 27, n.º 2 (marzo de 1996): 95. http://dx.doi.org/10.2307/2687396.

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2

Wampler, Joe F. y Stephen E. Newman. "Integer Programming". College Mathematics Journal 27, n.º 2 (marzo de 1996): 95–100. http://dx.doi.org/10.1080/07468342.1996.11973758.

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3

Cornu�jols, G�rard y William R. Pulleyblank. "Integer programming". Mathematical Programming 98, n.º 1-3 (1 de septiembre de 2003): 1–2. http://dx.doi.org/10.1007/s10107-003-0417-3.

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4

Kara, Imdat y Halil Ibrahim Karakas. "Integer Programming Formulations For The Frobenius Problem". International Journal of Pure Mathematics 8 (28 de diciembre de 2021): 60–65. http://dx.doi.org/10.46300/91019.2021.8.8.

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The Frobenius number of a set of relatively prime positive integers α1,α2,…,αn such that α1< α2< …< αn, is the largest integer that can not be written as a nonnegative integer linear combination of the given set. Finding the Frobenius number is known as the Frobenius problem, which is also named as the coin exchange problem or the postage stamp problem. This problem is closely related with the equality constrained integer knapsack problem. It is known that this problem is NP-hard. Extensive research has been conducted for finding the Frobenius number of a given set of positive integers. An exact formula exists for the case n=2 and various formulas have been derived for all special cases of n = 3. Many algorithms have been proposed for n≥4. As far as we are aware, there does not exist any integer programming approach for this problem which is the main motivation of this paper. We present four integer linear programming formulations about the Frobenius number of a given set of positive integers. Our first formulation is used to check if a given positive integer is the Frobenius number of a given set of positive integers. The second formulation aims at finding the Frobenius number directly. The third formulation involves the residue classes with respect to the least member of the given set of positive integers, where a residue table is computed comprising all values modulo that least member, and the Frobenius number is obtained from there. Based on the same approach underlying the third formulation, we propose our fourth formulation which produces the Frobenius number directly. We demonstrate how to use our formulations with several examples. For illustrative purposes, some computa-tional analysis is also presented.

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5

Freire, Alexandre S., Eduardo Moreno y Juan Pablo Vielma. "An integer linear programming approach for bilinear integer programming". Operations Research Letters 40, n.º 2 (marzo de 2012): 74–77. http://dx.doi.org/10.1016/j.orl.2011.12.004.

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6

He, Deng Xu y Liang Dong Qu. "Population Migration Algorithm for Integer Programming and its Application in Cutting Stock Problem". Advanced Materials Research 143-144 (octubre de 2010): 899–904. http://dx.doi.org/10.4028/www.scientific.net/amr.143-144.899.

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For integer programming, there exist some difficulties and problems for the direct applications of population migration algorithm (PMA) due to the variables belonging to the set of integers. In this paper, a novel PMA is proposed for integer programming which evolves on the set of integer space. Several functions and cutting stock problem simulation results show that the proposed algorithm is significantly superior to other algorithms.

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7

Gomory, Ralph E. "Early Integer Programming". Operations Research 50, n.º 1 (febrero de 2002): 78–81. http://dx.doi.org/10.1287/opre.50.1.78.17793.

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8

Feautrier, Paul. "Parametric integer programming". RAIRO - Operations Research 22, n.º 3 (1988): 243–68. http://dx.doi.org/10.1051/ro/1988220302431.

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9

Lee, Jon y Adam N. Letchford. "Mixed integer programming". Discrete Optimization 4, n.º 1 (marzo de 2007): 1–2. http://dx.doi.org/10.1016/j.disopt.2006.10.005.

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10

Onn, Shmuel. "Robust integer programming". Operations Research Letters 42, n.º 8 (diciembre de 2014): 558–60. http://dx.doi.org/10.1016/j.orl.2014.10.002.

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11

Bienstock, Daniel y William Cook. "Computational integer programming". Mathematical Programming 81, n.º 2 (abril de 1998): 147–48. http://dx.doi.org/10.1007/bf01581102.

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12

Schaefer, Andrew J. "Inverse integer programming". Optimization Letters 3, n.º 4 (16 de junio de 2009): 483–89. http://dx.doi.org/10.1007/s11590-009-0131-z.

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13

Lageweg, B. J., J. K. Lenstra, A. H. G. RinnooyKan, L. Stougie y A. H. G. Rinnooy Kan. "STOCHASTIC INTEGER PROGRAMMING BY DYNAMIC PROGRAMMING". Statistica Neerlandica 39, n.º 2 (junio de 1985): 97–113. http://dx.doi.org/10.1111/j.1467-9574.1985.tb01131.x.

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14

Williams, H. P. "Logic applied to integer programming and integer programming applied to logic". European Journal of Operational Research 81, n.º 3 (marzo de 1995): 605–16. http://dx.doi.org/10.1016/0377-2217(93)e0359-6.

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15

Fujiwara, Hiroshi, Hokuto Watari y Hiroaki Yamamoto. "Dynamic Programming for the Subset Sum Problem". Formalized Mathematics 28, n.º 1 (1 de abril de 2020): 89–92. http://dx.doi.org/10.2478/forma-2020-0007.

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SummaryThe subset sum problem is a basic problem in the field of theoretical computer science, especially in the complexity theory [3]. The input is a sequence of positive integers and a target positive integer. The task is to determine if there exists a subsequence of the input sequence with sum equal to the target integer. It is known that the problem is NP-hard [2] and can be solved by dynamic programming in pseudo-polynomial time [1]. In this article we formalize the recurrence relation of the dynamic programming.

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16

De Loera, Jesús A., Raymond Hemmecke, Shmuel Onn y Robert Weismantel. "N-fold integer programming". Discrete Optimization 5, n.º 2 (mayo de 2008): 231–41. http://dx.doi.org/10.1016/j.disopt.2006.06.006.

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17

Williams, H. P. y J. N. Hooker. "Integer programming as projection". Discrete Optimization 22 (noviembre de 2016): 291–311. http://dx.doi.org/10.1016/j.disopt.2016.08.004.

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18

Jan, Rong-Hong y Maw-Sheng Chern. "Nonlinear integer bilevel programming". European Journal of Operational Research 72, n.º 3 (febrero de 1994): 574–87. http://dx.doi.org/10.1016/0377-2217(94)90424-3.

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19

Dua, Vivek. "Mixed integer polynomial programming". Computers & Chemical Engineering 72 (enero de 2015): 387–94. http://dx.doi.org/10.1016/j.compchemeng.2014.07.020.

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20

Atamtürk, Alper y Martin W. P. Savelsbergh. "Integer-Programming Software Systems". Annals of Operations Research 140, n.º 1 (noviembre de 2005): 67–124. http://dx.doi.org/10.1007/s10479-005-3968-2.

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21

Weintraub P., Andres. "Integer programming in forestry". Annals of Operations Research 149, n.º 1 (2 de diciembre de 2006): 209–16. http://dx.doi.org/10.1007/s10479-006-0105-9.

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22

Firmansah, Fery, Muhammad Ridlo Yuwono y Fika Aisyah Munif. "Application of integer linear program in optimizing convection sector production results using branch and bound method". International Journal of Applied Mathematics, Sciences, and Technology for National Defense 1, n.º 1 (27 de enero de 2023): 13–20. http://dx.doi.org/10.58524/app.sci.def.v1i1.173.

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This study aimed to determine the application of the integer program in optimizing the production of the convection sector. Integer linear programming is a special form of linear programming in which the decision variable solutions are integers. Ayyumnah store as one part of the convection sectors with a home-scale does not have an appropriate strategy to optimize profits with limited materials owned. The method used in this study is an integer program with the branch and bound method. The result of this research is the optimal amount of production of long shirts and tunics at the Ayyumnah Store with maximum profit.

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23

Klamroth, Kathrin, Jørgen Tind y Sibylle Zust. "Integer Programming Duality in Multiple Objective Programming". Journal of Global Optimization 29, n.º 1 (mayo de 2004): 1–18. http://dx.doi.org/10.1023/b:jogo.0000035000.06101.07.

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24

Marchand, Hugues, Alexander Martin, Robert Weismantel y Laurence Wolsey. "Cutting planes in integer and mixed integer programming". Discrete Applied Mathematics 123, n.º 1-3 (noviembre de 2002): 397–446. http://dx.doi.org/10.1016/s0166-218x(01)00348-1.

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25

Gazzah, H. y A. K. Khandani. "Optimum non-integer rate allocation using integer programming". Electronics Letters 33, n.º 24 (1997): 2034. http://dx.doi.org/10.1049/el:19971417.

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26

Forrest, J. J. H. y J. A. Tomlin. "Branch and bound, integer, and non-integer programming". Annals of Operations Research 149, n.º 1 (2 de diciembre de 2006): 81–87. http://dx.doi.org/10.1007/s10479-006-0112-x.

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27

Domínguez, Luis F. y Efstratios N. Pistikopoulos. "Multiparametric programming based algorithms for pure integer and mixed-integer bilevel programming problems". Computers & Chemical Engineering 34, n.º 12 (diciembre de 2010): 2097–106. http://dx.doi.org/10.1016/j.compchemeng.2010.07.032.

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28

Maslikhah, Siti. "METODE PEMECAHAN MASALAH INTEGER PROGRAMMING". At-Taqaddum 7, n.º 2 (6 de febrero de 2017): 211. http://dx.doi.org/10.21580/at.v7i2.1203.

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<em>Decision variables in the problem solving linear programs are often in the form of fractions. In some cases there are specific desires the solution in the form of an integer (integer). Integer solution is obtained by way of rounding does not warrant being in the area of fisibel. To obtain integer solutions, among others, by the method of Cutting Plane Algorithm or Branch and Bound. The advantages of the method of Cutting Plane Algorithm is quite effectively shorten the matter, while the advantages of the method of Branch and Bound the error level is to have a little but requires quite a long calculation.</em>

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29

Earnshaw, Stephanie R. y Susan L. Dennett. "Integer/Linear Mathematical Programming Models". PharmacoEconomics 21, n.º 12 (2003): 839–51. http://dx.doi.org/10.2165/00019053-200321120-00001.

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30

Lee, D.-H., H.-J. Kim, G. Choi y P. Xirouchakis. "Disassembly scheduling: Integer programming models". Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 218, n.º 10 (octubre de 2004): 1357–72. http://dx.doi.org/10.1243/0954405042323586.

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31

Gavish, Bezalel, Fred Glover y Hasan Pirkul. "Surrogate Constraints in Integer Programming". Journal of Information and Optimization Sciences 12, n.º 2 (mayo de 1991): 219–28. http://dx.doi.org/10.1080/02522667.1991.10699064.

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32

Wilson, J. M. "Crossword Compilation Using Integer Programming". Computer Journal 32, n.º 3 (1 de marzo de 1989): 273–75. http://dx.doi.org/10.1093/comjnl/32.3.273.

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33

Feng, Zhiguo y Ka-Fai Cedric Yiu. "Manifold relaxations for integer programming". Journal of Industrial & Management Optimization 10, n.º 2 (2014): 557–66. http://dx.doi.org/10.3934/jimo.2014.10.557.

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34

Gupta, Renu y M. C. Puri. "Bicriteria integer quadratic programming problems". Journal of Interdisciplinary Mathematics 3, n.º 2-3 (junio de 2000): 133–48. http://dx.doi.org/10.1080/09720502.2000.10700277.

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35

Williams, H. "Integer programming and pricing revisited". IMA Journal of Management Mathematics 8, n.º 3 (1 de marzo de 1997): 203–13. http://dx.doi.org/10.1093/imaman/8.3.203.

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36

Hoşten, Serkan y Bernd Sturmfels. "Computing the integer programming gap". Combinatorica 27, n.º 3 (mayo de 2007): 367–82. http://dx.doi.org/10.1007/s00493-007-2057-3.

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37

Hua, Hao, Ludger Hovestadt, Peng Tang y Biao Li. "Integer programming for urban design". European Journal of Operational Research 274, n.º 3 (mayo de 2019): 1125–37. http://dx.doi.org/10.1016/j.ejor.2018.10.055.

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38

Gomory, Ralph E. y Ellis L. Johnson. "An approach to integer programming". Mathematical Programming 96, n.º 2 (1 de mayo de 2003): 181. http://dx.doi.org/10.1007/s10107-003-0382-x.

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39

Schultz, Rüdiger. "Stochastic programming with integer variables". Mathematical Programming 97, n.º 1 (julio de 2003): 285–309. http://dx.doi.org/10.1007/s10107-003-0445-z.

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40

Röglin, Heiko y Berthold Vöcking. "Smoothed analysis of integer programming". Mathematical Programming 110, n.º 1 (5 de enero de 2007): 21–56. http://dx.doi.org/10.1007/s10107-006-0055-7.

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41

Zou, Jikai, Shabbir Ahmed y Xu Andy Sun. "Stochastic dual dynamic integer programming". Mathematical Programming 175, n.º 1-2 (2 de marzo de 2018): 461–502. http://dx.doi.org/10.1007/s10107-018-1249-5.

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42

Klabjan, Diego. "Subadditive approaches in integer programming". European Journal of Operational Research 183, n.º 2 (diciembre de 2007): 525–45. http://dx.doi.org/10.1016/j.ejor.2006.10.009.

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43

Sahinidis, Nikolaos V. "Mixed-integer nonlinear programming 2018". Optimization and Engineering 20, n.º 2 (24 de abril de 2019): 301–6. http://dx.doi.org/10.1007/s11081-019-09438-1.

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44

Adams, Warren P. y Hanif D. Sherali. "Mixed-integer bilinear programming problems". Mathematical Programming 59, n.º 1-3 (marzo de 1993): 279–305. http://dx.doi.org/10.1007/bf01581249.

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45

Allahviranloo, T., Kh Shamsolkotabi, N. A. Kiani y L. Alizadeh. "Fuzzy integer linear programming problems". International Journal of Contemporary Mathematical Sciences 2 (2007): 167–81. http://dx.doi.org/10.12988/ijcms.2007.07010.

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46

Vessal, Ahmad. "COURSE SEQUENCING USING INTEGER PROGRAMMING". Journal of Academy of Business and Economics 13, n.º 4 (1 de octubre de 2013): 97–102. http://dx.doi.org/10.18374/jabe-13-4.10.

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47

Williams, H. P. "The problem with integer programming". IMA Journal of Management Mathematics 22, n.º 3 (5 de octubre de 2010): 213–30. http://dx.doi.org/10.1093/imaman/dpq014.

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48

Lovász, László. "Integer sequences and semidefinite programming". Publicationes Mathematicae Debrecen 56, n.º 3-4 (1 de abril de 2000): 475–79. http://dx.doi.org/10.5486/pmd.2000.2362.

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49

Labbé, Martine, Alfredo Marín y Antonio M. Rodríguez-Chía. "Lexicographical Order in Integer Programming". Vietnam Journal of Mathematics 45, n.º 3 (27 de julio de 2016): 459–76. http://dx.doi.org/10.1007/s10013-016-0220-0.

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50

Raghavan, Prabhakar. "Integer programming in VLSI design". Discrete Applied Mathematics 40, n.º 1 (noviembre de 1992): 29–43. http://dx.doi.org/10.1016/0166-218x(92)90020-b.

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