Relevant bibliographies by topics / Mathematical programming

Academic literature on the topic 'Mathematical programming'

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Published: 4 June 2021
Last updated: 7 July 2024

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Journal articles on the topic "Mathematical programming"

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Vasileva, Natalia, Vladimir Grigorev-Golubev, and Irina Evgrafova. "Mathematical programming in Mathcad and Mathematica." E3S Web of Conferences 419 (2023): 02007. http://dx.doi.org/10.1051/e3sconf/202341902007.

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An article generalizes the long-term work of authors with packages of applied mathematical programs. It discusses and demonstrates the features and methods of solution of mathematical tasks in mathematical package Mathcad and Mathematica: from the simplest ones, included in the set of typical problems of mathematical disciplines for training specialists for shipbuilding, to complex computational tasks and applied problems of professional orientation, which require the construction of a mathematical model and analysis of the results obtained. The examples show the solution of mathematical problems in symbolic form, mathematical studies in the Mathcad and Mathematica environment, and mathematical programming with these packages.
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Elphick, Clive, R. W. Cottle, M. L. Kelmanson, and B. Korte. "Mathematical Programming." Journal of the Operational Research Society 36, no. 4 (April 1985): 342. http://dx.doi.org/10.2307/2582424.

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Elphick, Clive. "Mathematical Programming." Journal of the Operational Research Society 36, no. 4 (April 1985): 342. http://dx.doi.org/10.1057/jors.1985.59.

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Wilson, J. M., K. L. Hoffman, R. H. F. Jackson, and J. Telgen. "Computational Mathematical Programming." Journal of the Operational Research Society 39, no. 8 (August 1988): 792. http://dx.doi.org/10.2307/2583777.

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Howitt, Richard E. "Positive Mathematical Programming." American Journal of Agricultural Economics 77, no. 2 (May 1995): 329–42. http://dx.doi.org/10.2307/1243543.

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Wilson, J. M. "Computational Mathematical Programming." Journal of the Operational Research Society 39, no. 8 (August 1988): 792. http://dx.doi.org/10.1057/jors.1988.137.

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Wasserman, A. L., and R. H. Eckhouse. "Mathematical-oriented programming." Computer 21, no. 6 (June 1988): 89–95. http://dx.doi.org/10.1109/2.954.

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Oley, L. A. "Mathematical programming techniques." European Journal of Operational Research 21, no. 1 (July 1985): 139–40. http://dx.doi.org/10.1016/0377-2217(85)90098-0.

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Sachs, E. "Computational mathematical programming." European Journal of Operational Research 39, no. 2 (March 1989): 227–28. http://dx.doi.org/10.1016/0377-2217(89)90199-9.

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Сальков and Nikolay Sal'kov. "Graph-analytic Solution of Some Special Problems of Quadratic Programming." Geometry & Graphics 2, no. 1 (March 3, 2014): 3–8. http://dx.doi.org/10.12737/3842.

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Quadratic programming problems are one of special cases of mathematical programming problems. Mathematical programming problems solution is of great importance, because these problems are those of optimizing of solution related to presented issues from multitude of possible ones. The mathematical programming problems are linear, nonlinear, dynamic and others. It is suggested to consider a graph-analytic solution of quadratic programming’s special problems, which, taken together, constitute the quadratic programming problems for two and three variables. A total of eight special problems have been considered.
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Dissertations / Theses on the topic "Mathematical programming"

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Koch, Thorsten. "Rapid mathematical programming." [S.l.] : [s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=973541415.

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Moreno, Dávila Julio Moreno Davila Julio. "Mathematical programming for logic inference /." [S.l.] : [s.n.], 1990. http://library.epfl.ch/theses/?nr=784.

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Sharifi, Mokhtarian Faranak. "Mathematical programming with LFS functions." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=56762.

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Differentiable functions with a locally flat surface (LFS) have been recently introduced and studied in convex optimization. Here we extend this motion in two directions: to non-smooth convex and smooth generalized convex functions. An important feature of these functions is that the Karush-Kuhn-Tucker condition is both necessary and sufficient for optimality. Then we use the properties of linear LFS functions and basic point-to-set topology to study the "inverse" programming problem. In this problem, a feasible, but nonoptimal, point is made optimal by stable perturbations of the parameters. The results are applied to a case study in optimal production planning.
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Steffy, Daniel E. "Topics in exact precision mathematical programming." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39639.

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The focus of this dissertation is the advancement of theory and computation related to exact precision mathematical programming. Optimization software based on floating-point arithmetic can return suboptimal or incorrect resulting because of round-off errors or the use of numerical tolerances. Exact or correct results are necessary for some applications. Implementing software entirely in rational arithmetic can be prohibitively slow. A viable alternative is the use of hybrid methods that use fast numerical computation to obtain approximate results that are then verified or corrected with safe or exact computation. We study fast methods for sparse exact rational linear algebra, which arises as a bottleneck when solving linear programming problems exactly. Output sensitive methods for exact linear algebra are studied. Finally, a new method for computing valid linear programming bounds is introduced and proven effective as a subroutine for solving mixed-integer linear programming problems exactly. Extensive computational results are presented for each topic.
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Smith, Barbara Mary. "Bus crew scheduling using mathematical programming." Thesis, University of Leeds, 1986. http://etheses.whiterose.ac.uk/1053/.

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This thesis describes a bus crew scheduling system, IMPACS, which has been demonstrated to be successful for a wide variety of scheduling conditions, and is at present in regular use by three British bus companies including the largest, London Buses Ltd. The background to the bus crew scheduling problem 1S described and the existing literature on methods for solution is reviewed. In IMPACS, the crew scheduling problem is formulated as an integer linear programme using a formulation which is an extension of set covering; a very large set of possible duties is generated, from which the duties forming the schedule are selected in such a way as to minimise the total cost. The variables of the set covering problem correspond to the duties generated and the constraints to the pieces of work in the bus schedule. For realistic schedules, it is impossible to generate all legal duties, and there are often too many pieces of work to allow each one to give rise to a constraint. IMPACS contains several heuristic methods which reduce the set covering problem to a manageable size, while still allowing good quality schedules to be compiled. Techniques for speeding up the solution of the set covering problem have been investigated, and in particular a branching strategy which exploits features of the crew scheduling problem has been developed.
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Aras, Raghav. "Mathematical programming methods for decentralized POMDPs." Thesis, Nancy 1, 2008. http://www.theses.fr/2008NAN10092/document.

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Nous étudions le problème du contrôle optimale décentralisé d'un processus de Markoff partiellement observé sur un horizon fini. Mathématiquement, ce problème se défini comme un DEC-POMDP. Plusieurs problèmes des domaines de l'intélligence artificielles et recherche opérationelles se formalisent comme des DEC-POMDPs. Résoudre un DEC-POMDP dans une mannière exacte est un problème difficile (NEXP-dur). Pourtant, des algorithmes exactes sont importants du point de vue des algorithmes approximés pour résoudre des problèmes pratiques. Les algorithmes existants sont nettement inefficace même pour des DEC-POMDP d'une très petite taille. Dans cette thèse, nous proposons une nouvelle approche basée sur la programmation mathématique. En utilisant la forme séquentielle d'une politique, nous montrons que ce problème peut être formalisé comme un programme non-linéaire. De plus, nous montrons comment transformer ce programme nonl-linéaire un des programmes linéaire avec des variables bivalents et continus (0-1 MIPs). L'éxpérience computationelle sur quatres problèmes DEC-POMDP standards montrent que notre approche trouve une politique optimale beaucoup plus rapidement que des approches existantes. Le temps réduit des heures aux seconds ou minutes
In this thesis, we study the problem of the optimal decentralized control of a partially observed Markov process over a finite horizon. The mathematical model corresponding to the problem is a decentralized POMDP (DEC-POMDP). Many problems in practice from the domains of artificial intelligence and operations research can be modeled as DEC-POMDPs. However, solving a DEC-POMDP exactly is intractable (NEXP-hard). The development of exact algorithms is necessary in order to guide the development of approximate algorithms that can scale to practical sized problems. Existing algorithms are mainly inspired from POMDP research (dynamic programming and forward search) and require an inordinate amount of time for even very small DEC-POMDPs. In this thesis, we develop a new mathematical programming based approach for exactly solving a finite horizon DEC-POMDP. We use the sequence form of a control policy in this approach. Using the sequence form, we show how the problem can be formulated as a mathematical progam with a nonlinear object and linear constraints. We thereby show how this nonlinear program can be linearized to a 0-1 mixed integer linear program (MIP). We present two different 0-1 MIPs based on two different properties of a DEC-POMDP. The computational experience of the mathematical programs presented in the thesis on four benchmark problems (MABC, MA-Tiger, Grid Meeting, Fire Fighting) shows that the time taken to find an optimal joint policy is one or two orders or magnitude lesser than the exact existing algorithms. In the problems tested, the time taken drops from several hours to a few seconds or minutes
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Aras, Raghav Charpillet François Dutech Alain. "Mathematical programming methods for decentralized POMDPs." S. l. : Nancy 1, 2008. http://www.scd.uhp-nancy.fr/docnum/SCD_T_2008_0092_ARAS.pdf.

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Hochreiter, Ronald. "Applied Mathematical Programming and Modelling 2016." edp sciences, 2017. http://dx.doi.org/10.1051/itmconf/20171400001.

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The 12th International Conference on Applied Mathematical Programming and Modelling (APMOD 2016) was held in Brno, Czech Republic in June 8-10, 2016. In this volume eight research papers are collected which depict the broad range of topics the conference series covers.
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Reeves, Laurence H. "Mathematical Programming Applications in Agroforestry Planning." DigitalCommons@USU, 1991. https://digitalcommons.usu.edu/etd/6495.

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Agroforestry as a sustainable production system has been recognized as a land use system with the potential to slow encroachment of agriculture onto forested lands in developing countries. However, the acceptance of nontraditional agroforestry systems has been hampered in some areas due to the risk-averse nature of rural agriculturalists. By explicitly recognizing risk in agroforestry planning, a wider acceptance of agroforestry is possible. This thesis consists of a collection of three papers that explore the potential of modern stock portfolio theory to reduce financial risk in agroforestry planning. The first paper presents a theoretical framework that incorporates modern stock portfolio theory through mathematical programming. This framework allows for the explicit recognition of financial risk by using a knowledge of past net revenue trends and fluctuations for various cropping systems, with the assumption that past trend behavior is indicative of future behavior. The paper demonstrates how financial risk can be reduced by selecting cropping systems with stable and/or negatively correlated net revenues, thereby reducing the variance of future net revenues. Agroforestry systems generally entail growing simultaneously some combination of plant and/or animal species. As a result, interactions between crops usually cause crop yields within systems to deviate from what would be observed under monocultural conditions, thus requiring some means of incorporating these interactions into mathematical models. The second paper presents two approaches to modeling such interactions, depending on the nature of the interaction. The continuous system approach is appropriate under conditions where yield interactions are linear between crops and allows for a continuous range of crop mixtures. The discrete system approach should be used where nonlinear interactions occur. Under this second approach, decision variables are defined as fixed crop mixtures with known yields. In the third paper, the techniques presented above were applied to a case study site in Costa Rica. Using MOTAD programming and a discrete system approach, a set of minimum-risk farm plans were derived for a hypothetical farm. For the region studied, results indicate that reductions in risk require substantial reductions in expected net revenue.
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Violin, Alessia. "Mathematical programming approaches to pricing problems." Doctoral thesis, Università degli studi di Trieste, 2014. http://hdl.handle.net/10077/10863.

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2012/2013
There are many real cases where a company needs to determine the price of its products so as to maximise its revenue or profit. To do so, the company must consider customers’ reactions to these prices, as they may refuse to buy a given product or service if its price is too high. This is commonly known in literature as a pricing problem. This class of problems, which is typically bilevel, was first studied in the 1990s and is NP-hard, although polynomial algorithms do exist for some particular cases. Many questions are still open on this subject. The aim of this thesis is to investigate mathematical properties of pricing problems, in order to find structural properties, formulations and solution methods that are as efficient as possible. In particular, we focus our attention on pricing problems over a network. In this framework, an authority owns a subset of arcs and imposes tolls on them, in an attempt to maximise his/her revenue, while users travel on the network, seeking for their minimum cost path. First, we provide a detailed review of the state of the art on bilevel pricing problems. Then, we consider a particular case where the authority is using an unit toll scheme on his/her subset of arcs, imposing either the same toll on all of them, or a toll proportional to a given parameter particular to each arc (for instance a per kilometre toll). We show that if tolls are all equal then the complexity of the problem is polynomial, whereas in case of proportional tolls it is pseudo-polynomial. We then address a robust approach taking into account uncertainty on parameters. We solve some polynomial cases of the pricing problem where uncertainty is considered using an interval representation. Finally, we focus on another particular case where toll arcs are connected such that they constitute a path, as occurs on highways. We develop a Dantzig-Wolfe reformulation and present a Branch-and-Cut-and-Price algorithm to solve it. Several improvements are proposed, both for the column generation algorithm used to solve the linear relaxation and for the branching part used to find integer solutions. Numerical results are also presented to highlight the efficiency of the proposed strategies. This problem is proved to be APX-hard and a theoretical comparison between our model and another one from the literature is carried out.
Un problème classique pour une compagnie est la tarification de ses produits à vendre sur le marché, de façon à maximiser les revenus. Dans ce contexte, il est important que la société prenne en compte le comportement de ses clients potentiels, puisque si le prix est trop élevé, ils peuvent décider de ne rien acheter. Ce problème est communément connu dans la littérature comme un problème de tarification ou "pricing". Une approche de programmation biniveau pour ce problème a été introduite dans les années 90, révélant sa difficulté. Cependant, certains cas particuliers peuvent être résolus par des algorithmes polynomiaux, et il y a encore de nombreuses questions ouvertes sur le sujet. Cette thèse de doctorat porte sur les propriétés mathématiques des problèmes de tarification, fixant l’objectif de déterminer différentes formulations et méthodes de résolution les plus efficaces possibles, en se concentrant sur les problèmes appliqués aux réseaux de différents types. Dans les problèmes de tarification sur réseau, nous avons deux entités : une autorité qui possède un certain sous-ensemble d’arcs, et impose des péages, avec l’intention de maximiser les revenus provenant de celle-ci, et des utilisateurs qui choisissent leur chemin de moindre coût sur l’ensemble du réseau. Dans la première partie de la thèse une analyse détaillée de l’état de l’art sur les problèmes de tarification biniveau est présentée, suivie, dans la deuxième partie, par une analyse de cas particuliers polynomiaux. En particulier, nous considérons le cas où l’autorité utilise un péage unitaire sur son sous-ensemble d’arcs, soit en choisissant le même péage sur chaque arc, soit en choisissant un péage proportionnel à un paramètre donné pour chaque arc (par exemple, un péage par kilomètre). Dans le premier cas de péages égaux, il est démontré que la complexité du problème est polynomiale, tandis que dans le second cas de péages proportionnels, elle est pseudo-polynomiale. Ensuite, nous présentons une première approche d’optimisation robuste pour les problèmes de tarification sur réseau, de manière à inclure de l’incertitude sur la valeur exacte des paramètres dans le modèle, qui est typique dans les problèmes réels. Cette incertitude est représentée en utilisant des intervalles pour les paramètres et nous proposons, pour certains cas, des algorithmes de résolution polynomiaux. La troisième et dernière partie de la thèse concerne un cas difficile, le problème de tarification sur réseau dans lequel les arcs sont connectés de manière à constituer un chemin, comme c’est le cas pour les autoroutes. Initialement, nous prouvons que ce problème est APX-dur, renforçant le résultat connu jusqu’à maintenant. Ensuite, nous présentons des nouvelles formulations plus fortes, et en particulier, nous développons une reformulation de type Danztig-Wolfe, résolue par un algorithme de Branch-and-Cut-and-Price. Enfin, nous proposons différentes stratégies pour améliorer les performances de l’algorithme, pour ce qui concerne l’algorithme de génération de colonnes utilisé pour résoudre la relaxation linéaire, et pour ce qui concerne la résolution du problème avec variables binaires. Les résultats numériques complètent les résultats théoriques, en mettant en évidence l’efficacité des stratégies proposées.
Un classico problema aziendale è la determinazione del prezzo dei prodotti da vendere sul mercato, in modo tale da massimizzare le entrate che ne deriveranno. In tale contesto è importante che l’azienda tenga in considerazione il comportamento dei propri potenziali clienti, in quanto questi ultimi potrebbero ritenere che il prezzo sia troppo alto e decidere dunque di non acquistare. Questo problema è comunemente noto in letteratura come problema di tariffazione o di “pricing”. Tale problema è stato studiato negli anni novanta mediante un approccio bilivello, rivelandone l’alta complessità computazionale. Tuttavia alcuni casi particolari possono essere risolti mediante algoritmi polinomiali, e ci sono sono ancora molte domande aperte sull’argomento. Questa tesi di dottorato si focalizza sulle proprietà matematiche dei problemi di tariffazione, ponendosi l’obiettivo di determinarne formulazioni e metodi risolutivi più efficienti possibili, concentrandosi sui problemi applicati a reti di vario tipo. Nei problemi di tariffazione su rete si hanno due entità: un’autorità che possiede un certo sottoinsieme di archi e vi impone dei pedaggi, con l’intento di massimizzare le entrate che ne derivano, e gli utenti che scelgono il proprio percorso a costo minimo sulla rete complessiva (a pedaggio e non). Nella prima parte della tesi viene affrontata una dettagliata analisi dello stato dell’arte sui problemi di tariffazione bilivello, seguita, nella seconda parte, dall’analisi di particolari casi polinomiali del problema. In particolare si considera il caso in cui l’autorità utilizza uno schema di pedaggio unitario sul suo sottoinsieme di archi, imponendo o lo stesso pedaggio su ogni arco, o un pedaggio proporzionale a un dato parametro relativo ad ogni arco (ad esempio un pedaggio al chilometro). Nel primo caso di pedaggi uguali, si dimostra che la complessità del problema è polinomiale, mentre nel secondo caso di pedaggi proporzionali è pseudo-polinomiale. In seguito viene affrontato un approccio di ottimizzazione robusta per alcuni problemi di tariffazione su rete, in modo da includere nei modelli un’incertezza sul valore esatto dei parametri,tipica dei problemi reali. Tale incertezza viene rappresentata vincolando i parametri in degli intervalli e si propongono, per alcuni casi, algoritmi risolutivi polinomiali. La terza e ultima parte della tesi riguarda un caso computazionalmente difficile, in cui gli archi tariffabili sono connessi in modo tale da costituire un cammino, come avviene per le autostrade. Inizialmente si dimostra che tale problema è APX-hard, rafforzando il risultato finora conosciuto. In seguito si considerano formulazioni piùforti, e in particolare si sviluppa una riformulazione di Danztig-Wolfe, risolta tramite un algoritmo di Branch-and-Cut-and-Price. Infine si propongono diverse strategie per migliorare le performance dell’algoritmo, sia per quanto riguarda l’algoritmo di generazione di colonne utilizzato per risolvere il rilassamento lineare, sia per quanto riguarda la risoluzione del problema con variabili binarie. Risultati numerici complementano quelli teorici ed evidenziano l’efficacia delle strategie proposte.
XXV Ciclo
1985
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Books on the topic "Mathematical programming"

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Vajda, S. Mathematical programming. Mineola, N.Y: Dover Publications, 2009.

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Karmanov, V. G. Mathematical programming. Moscow: Mir Publishers, 1989.

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Mathematical programming. Mineola, N.Y: Dover Publications, 2009.

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D, Lawrence Kenneth, ed. Mathematical programming. Amsterdam: JAI/Elsevier, 2004.

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Hoffman, K. L., R. H. F. Jackson, and J. Telgen, eds. Computation Mathematical Programming. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/bfb0121175.

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Schittkowski, Klaus, ed. Computational Mathematical Programming. Berlin, Heidelberg: Springer Berlin Heidelberg, 1985. http://dx.doi.org/10.1007/978-3-642-82450-0.

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Lai, Young-Jou, and Ching-Lai Hwang. Fuzzy Mathematical Programming. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-48753-8.

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Mathematical programming applications. New York: Macmillan, 1987.

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1946-, Schittkowski Klaus, and North Atlantic Treaty Organization. Scientific Affairs Division., eds. Computational mathematical programming. Berlin: Springer-Verlag, 1985.

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L, Hoffman K., Jackson Richard Henry Frymuth, Telgen J, Mathematical Programming Society (U.S.). Committee on Algorithms., and NATO Advanced Study Institute on Computational Mathematical Programming (1984 : Bad Windsheim, Germany), eds. Computational mathematical programming. Amsterdam: North-Holland, 1987.

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Book chapters on the topic "Mathematical programming"

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Shekhar, Shashi, and Hui Xiong. "Mathematical Programming." In Encyclopedia of GIS, 651. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_762.

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Liu, Baoding. "Mathematical Programming." In Theory and Practice of Uncertain Programming, 1–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89484-1_1.

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Valliant, Richard, Jill A. Dever, and Frauke Kreuter. "Mathematical Programming." In Statistics for Social and Behavioral Sciences, 129–68. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-93632-1_5.

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Johnson, Ellis L. "Mathematical Programming." In Operations Research Proceedings, 7. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-642-74862-2_3.

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Smith, D. Lloyd. "Mathematical Programming." In Mathematical Programming Methods in Structural Plasticity, 1–21. Vienna: Springer Vienna, 1990. http://dx.doi.org/10.1007/978-3-7091-2618-9_1.

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Belenky, Alexander S. "Mathematical Programming." In Applied Optimization, 13–90. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4757-6075-0_2.

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Valliant, Richard, Jill A. Dever, and Frauke Kreuter. "Mathematical Programming." In Practical Tools for Designing and Weighting Survey Samples, 129–61. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6449-5_5.

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Wang, Lin. "Mathematical Programming." In Encyclopedia of Systems Biology, 1185–86. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_405.

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Weik, Martin H. "mathematical programming." In Computer Science and Communications Dictionary, 985. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11178.

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Khan, Aman. "Mathematical Programming." In Cost and Optimization in Government, 197–236. Second Edition. | New York : Routledge, 2017. | Series: Public Administration and Public Policy | Previous edition: 2000.: Routledge, 2017. http://dx.doi.org/10.4324/9781315207674-7.

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Conference papers on the topic "Mathematical programming"

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Jing Gong and Jiaqi Ji. "Integration of Constraint Programming and mathematical programming." In 2010 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE 2010). IEEE, 2010. http://dx.doi.org/10.1109/icacte.2010.5579785.

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Zhaotao Yin and Tieke Li. "The integration of constraint programming and mathematical programming." In 2008 IEEE International Conference on Service Operations and Logistics, and Informatics. IEEE, 2008. http://dx.doi.org/10.1109/soli.2008.4682825.

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Messac, Achille, Emanuel Melachrinoudis, and Cyriaque Sukam. "Physical programming - A mathematical perspective." In 38th Aerospace Sciences Meeting and Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-686.

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Lent, Arnold. "Phase Recovery Via Mathematical Programming." In 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, edited by William A. Pearlman. SPIE, 1989. http://dx.doi.org/10.1117/12.970160.

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Shir, Ofer M. "Introductory mathematical programming for EC." In GECCO '20: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3377929.3389869.

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Shir, Ofer M. "Introductory mathematical programming for EC." In GECCO '18: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3205651.3207871.

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Shir, Ofer M. "Introductory mathematical programming for EC." In GECCO '21: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3449726.3461409.

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Shir, Ofer M. "Introductory mathematical programming for EC." In GECCO '22: Genetic and Evolutionary Computation Conference. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3520304.3533630.

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Wang, Ganming. "Mathematical programming applications in finance." In Second International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2022), edited by Shi Jin and Wanyang Dai. SPIE, 2023. http://dx.doi.org/10.1117/12.2672763.

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Ambrus-Somogyi, K. "Mathematical programming in the engineering education." In 2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics (SISY). IEEE, 2012. http://dx.doi.org/10.1109/sisy.2012.6339562.

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Reports on the topic "Mathematical programming"

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Mamgasarian, Olivi L. Machine Learning via Mathematical Programming. Fort Belvoir, VA: Defense Technical Information Center, November 1999. http://dx.doi.org/10.21236/ada382583.

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Ho, James K. Nonprocedural Implementation of Mathematical Programming Algorithms. Fort Belvoir, VA: Defense Technical Information Center, December 1988. http://dx.doi.org/10.21236/ada203392.

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Macal, C. M., and A. P. Hurter. Solution of mathematical programming formulations of subgame perfect equilibrium problems. Office of Scientific and Technical Information (OSTI), February 1992. http://dx.doi.org/10.2172/10134527.

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Goldfarb, Donald, and Garud Iyengar. Algorithms for Mathematical Programming with Emphasis on Bi-level Models. Office of Scientific and Technical Information (OSTI), May 2014. http://dx.doi.org/10.2172/1132080.

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Xu, Li. Fuzzy multiobjective mathematical programming in economic systems analysis: design and method. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.471.

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Shokaliuk, Svitlana V., Yelyzaveta Yu Bohunenko, Iryna V. Lovianova, and Mariya P. Shyshkina. Technologies of distance learning for programming basics lessons on the principles of integrated development of key competences. [б. в.], July 2020. http://dx.doi.org/10.31812/123456789/3888.

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In the era of the fourth industrial revolution – Industry 4.0 – developing key competences (digital, multilingual and mathematical competences in particular) is of paramount importance. The purpose of this work is to investigate the content of key competences of a secondary school student and to develop a method of teaching for the integrated development of multilingual and mathematical competences in the process of teaching Programming Basics with the help of distant technologies. The objectives of the research include generalizing and systematizing theoretical data on the structure and the content of key competences and the potential of informatics lessons for the development of separate components of multilingual and mathematical competences; generalizing and systematizing theoretical data on the ways of arranging distant support for informatics learning, Programming Basics in particular; to investigate the content and the methods of teaching Programming Basics in 7th-11th grades; to develop the e-learning Moodle course using Python for Programming Basics on the principles of integrated approach to developing separate components of multilingual and mathematical competence with determining some methodical special features while using it. The object of the study is to teach informatics to junior high school and high school students. The subject of the study is the means and the methods of realizing distant support in the process of teaching Programming Basics using Python on the principles of an integrated approach to developing multilingual and mathematical competences.
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Knighton, Shane A. A Network-Based Mathematical Programming Approach to Optimal Rostering of Continuous Heterogeneous Workforces. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada433267.

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Goldfarb, D. Algorithms for mathematical programming. Annual technical progress report, June 15, 1993--June 14, 1994. Office of Scientific and Technical Information (OSTI), June 1994. http://dx.doi.org/10.2172/10159667.

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Rioux, Bertrand, Abdullah Al Jarboua, Frederic Murphy, and Axel Pierru. Implementing Alternative Pricing Policies in Economic Equilibrium Models Using the Extended Mathematical Programming Framework. King Abdullah Petroleum Studies and Research Center, March 2020. http://dx.doi.org/10.30573/ks--2020mp01.

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Wang, Zhi, Mark Gehlhar, and Shunli Yao. Reconciling Trade Statistics from China, Hong Kong and Their Major Trading Partners--A Mathematical Programming Approach. GTAP Technical Paper, September 2007. http://dx.doi.org/10.21642/gtap.tp27.

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This paper develops a mathematical programming model to simultaneously estimate re-export markups and reconcile bilateral trade statistics between China, Hong Kong, and their trading partners. The model is applied to sector level trade flows to resolve discrepant reporting in an efficient manner. Adjustments in trade flows are based upon statistical reporters’ reliability information. The program is implemented in GAMS and retains many desirable theoretical and empirical properties. Estimates are used for generating trade flows and markups for Hong Kong’s re-exports used in the forthcoming version 7 GTAP database. The model’s flexibility has potential for expanded use in other regions where re-exports and associated markup cause discrepant trade flows.
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