Relevant bibliographies by topics / Min-max methods

Academic literature on the topic 'Min-max methods'

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Published: 14 March 2023

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Journal articles on the topic "Min-max methods"

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Lin, JiGuan G. "On min-norm and min-max methods of multi-objective optimization." Mathematical Programming 103, no. 1 (September 1, 2003): 1–33. http://dx.doi.org/10.1007/s10107-003-0462-y.

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Karadimitriou, Kosmas, and John M. Tyler. "Min-max compression methods for medical image databases." ACM SIGMOD Record 26, no. 1 (March 1997): 47–52. http://dx.doi.org/10.1145/248603.248613.

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Sun, Qiwei, Toshiyuki Miyamoto, Shoichi Kitamura, Ayako Taniguchi-Matsuoka, Kento Naito, Kazuyuki Mori, and Yoshio Izui. "Local Search Methods for Min-Max Clearing Problem." Transactions of the Institute of Systems, Control and Information Engineers 35, no. 8 (August 15, 2022): 193–201. http://dx.doi.org/10.5687/iscie.35.193.

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Tigan, Stephan, and I. M. Stancu-Minasian. "Methods for solving stochastic bilinear fractional max-min problems." RAIRO - Operations Research 30, no. 1 (1996): 81–98. http://dx.doi.org/10.1051/ro/1996300100811.

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Lu, Baiquan, Yuan Cao, Min jie Yuan, and Jianzhen Zhou. "Reference variable methods of solving min–max optimization problems." Journal of Global Optimization 42, no. 1 (July 12, 2007): 1–21. http://dx.doi.org/10.1007/s10898-007-9191-8.

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Sinsomboonthong, Saichon. "Performance Comparison of New Adjusted Min-Max with Decimal Scaling and Statistical Column Normalization Methods for Artificial Neural Network Classification." International Journal of Mathematics and Mathematical Sciences 2022 (April 22, 2022): 1–9. http://dx.doi.org/10.1155/2022/3584406.

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In this research, the normalization performance of the proposed adjusted min-max methods was compared to the normalization performance of statistical column, decimal scaling, adjusted decimal scaling, and min-max methods, in terms of accuracy and mean square error of the final classification outcomes. The evaluation process employed an artificial neural network classification on a large variety of widely used datasets. The best method was min-max normalization, providing 84.0187% average ranking of accuracy and 0.1097 average ranking of mean square error across all six datasets. However, the proposed adjusted-2 min-max normalization achieved a higher accuracy and a lower mean square error than min-max normalization on each of the following datasets: white wine quality, Pima Indians diabetes, vertical column, and Indian liver disease datasets. For example, the proposed adjusted-2 min-max normalization on white wine quality dataset achieved 100% accuracy and 0.00000282 mean square error. To conclude, for some classification applications on one of these specific datasets, the proposed adjusted-2 min-max normalization should be used over the other tested normalization methods because it performed better.
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Ginting, Raheliya Br. "Analisis Fungsi Implikasi Max-Min dan Max-Prod Dalam Pengambilan Keputusan." Creative Information Technology Journal 1, no. 2 (April 2, 2015): 128. http://dx.doi.org/10.24076/citec.2014v1i2.16.

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Pengambilan keputusan harus dilakukan berdasarkan pertimbangan-pertimbangan tertentu agar keputusan yang diambil dapat bersifat objektif, karena pengambilan keputusan yang dilakukan tanpa pertimbangan yang benar dapat mengakibatkan keputusan yang diambil menjadi kurang objektif. Logika fuzzy merupakan salah satu metode untuk melakukan analisis sistem yang mengandung ketidakpastian. Pada penelitian ini digunakan metode mamdani dengan fungsi implikasi Min dan Prod dan defuzzifikasi dilakukan dengan menggunakan metode centroid. Dari analisis yang telah dilakukan maka didapatkan output dengan fungsi implikasi Max-Prod lebih besar dibanding Max-Min, maka sebelum menyelesaikan suatu kasus seharusnya dilakukan pertimbangan terhadap pemilihan fungsi implikasi yang sesuai.Decision-making should be performed based on the certain considerations in order to obtain objective decisions since the decision made without proper consideration can lead to less objective. Fuzzy logic is one of the methods for analyzing systems that contain uncertainty. In this reserch, we use implication functions Min and Prod in Mamdani method and defuzzifikasi performed by using the centroid method. From the earlier analysis done, we obtained the final results of Max-Min and Max-Prod where the Max-Prod implication functions manually produces the greater value than Max-Min, then before completing a case consideration should be done to the selection of an appropriate implication function.
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Yildirim, M. "Analog circuit architecture for max and min pooling methods on image." Analog Integrated Circuits and Signal Processing 108, no. 1 (May 5, 2021): 119–24. http://dx.doi.org/10.1007/s10470-021-01842-x.

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David, Jennifer, and Thorsteinn Rögnvaldsson. "Multi-Robot Routing Problem with Min–Max Objective." Robotics 10, no. 4 (November 9, 2021): 122. http://dx.doi.org/10.3390/robotics10040122.

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In this paper, we study the “Multi-Robot Routing problem” with min–max objective (MRR-MM) in detail. It involves the assignment of sequentially ordered tasks to robots such that the maximum cost of the slowest robot is minimized. The problem description, the different types of formulations, and the methods used across various research communities are discussed in this paper. We propose a new problem formulation by treating this problem as a permutation matrix. A comparative study is done between three methods: Stochastic simulated annealing, deterministic mean-field annealing, and a heuristic-based graph search method. Each method is investigated in detail with several data sets (simulation and real-world), and the results are analysed and compared with respect to scalability, computational complexity, optimality, and its application to real-world scenarios. The paper shows that the heuristic method produces results very quickly with good scalability. However, the solution quality is sub-optimal. On the other hand, when optimal or near-optimal results are required with considerable computational resources, the simulated annealing method proves to be more efficient. However, the results show that the optimal choice of algorithm depends on the dataset size and the available computational budget. The contribution of the paper is three-fold: We study the MRR-MM problem in detail across various research communities. This study also shows the lack of inter-research terminology that has led to different names for the same problem. Secondly, formulating the task allocation problem as a permutation matrix formulation has opened up new approaches to solve this problem. Thirdly, we applied our problem formulation to three different methods and conducted a detailed comparative study using real-world and simulation data.
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Wei, Hong Yun, Zhong Xun Zhu, Yue Gang Tao, and Wen De Chen. "Output Feedback Assignability for Nonlinear Min-Max Systems." Advanced Materials Research 314-316 (August 2011): 374–79. http://dx.doi.org/10.4028/www.scientific.net/amr.314-316.374.

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This paper investigates the output feedback cycle time assignability of the min-max systems which are more complex than the systems studied in recent years. Max-plus projection representation for the closed-loop system with min-max output feedback is introduced. The coloring graph is presented and applied to analyze the structure of systems effectively. The necessary and sufficient criterion for the output feedback cycle time assignability is established which is an extension of the results studied before. The methods are constructive in nature.
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Dissertations / Theses on the topic "Min-max methods"

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Siddique, Muhammad. "Fuzzy decision making using max-min and MMR methods." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3042.

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Fuzzy logic is based on the theory of fuzzy sets, where an object’s membership of a set is gradual rather than just member or not a member. Fuzzy logic uses the whole interval of real numbers between zero (False) and one (True) to develop a logic as a basis for rules of inference. Particularly the fuzzified version of the modus ponens rule of inference enables computers to make decisions using fuzzy reasoning rather than exact. We study decision making problem under uncertainty. we analyze Max-Min method and Minimization of regret method originally developed by Savage and further developed by Yager. We generalize The MMR method by creating the parameterized family of minimum regret methods by using the ordered weighted averaging OWA operators.
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Chai, Qinqin. "Computational methods for solving optimal industrial process control problems." Thesis, Curtin University, 2013. http://hdl.handle.net/20.500.11937/1227.

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In this thesis, we develop new computational methods for three classes of dynamic optimization problems: (i) A parameter identification problem for a general nonlinear time-delay system; (ii) an optimal control problem involving systems with both input and output delays, and subject to continuous inequality state constraints; and (iii) a max-min optimal control problem arising in gradient elution chromatography.In the first problem, we consider a parameter identification problem involving a general nonlinear time-delay system, where the unknown time delays and system parameters are to be identified. This problem is posed as a dynamic optimization problem, where its cost function is to measure the discrepancy between predicted output and observed system output. The aim is to find unknown time-delays and system parameters such that the cost function is minimized. We develop a gradient-based computational method for solving this dynamic optimization problem. We show that the gradients of the cost function with respect to these unknown parameters can be obtained via solving a set of auxiliary time-delay differential systems from t = 0 to t = T. On this basis, the parameter identification problem can be solved as a nonlinear optimization problem and existing optimization techniques can be used. Two numerical examples are solved using the proposed computational method. Simulation results show that the proposed computational method is highly effective. In particular, the convergence is very fast even when the initial guess of the parameter values is far away from the optimal values.Unlike the first problem, in the second problem, we consider a time delay identification problem, where the input function for the nonlinear time-delay system is piecewise-constant. We assume that the time-delays—one involving the state variables and the other involving the input variables—are unknown and need to be estimated using experimental data. We also formulate the problem of estimating the unknown delays as a nonlinear optimization problem in which the cost function measures the least-squares error between predicted output and measured system output. This estimation problem can be viewed as a switched system optimal control problem with time-delays. We show that the gradient of the cost function with respect to the unknown state delay can be obtained via solving a auxiliary time-delay differential system. Furthermore, the gradient of the cost function with respect to the unknown input delay can be obtained via solving an auxiliary time-delay differential system with jump conditions at the delayed control switching time points. On this basis, we develop a heuristic computational algorithm for solving this problem using gradient based optimization algorithms. Time-delays in two industrial processes are estimated using the proposed computational method. Simulation results show that the proposed computational method is highly effective.For the third problem, we consider a general optimal control problem governed by a system with input and output delays, and subject to continuous inequality constraints on the state and control. We focus on developing an effective computational method for solving this constrained time delay optimal control problem. For this, the control parameterization technique is used to approximate the time planning horizon [0, T] into N subintervals. Then, the control is approximated by a piecewise constant function with possible discontinuities at the pre-assigned partition points, which are also called the switching time points. The heights of the piecewise constant function are decision variables which are to be chosen such that a given cost function is minimized. For the continuous inequality constraints on the state, we construct approximating smooth functions in integral form. Then, the summation of these approximating smooth functions in integral form, which is called the constraint violation, is appended to the cost function to form a new augmented cost function. In this way, we obtain a sequence of approximate optimization problems subject to only boundedness constraints on the decision variables. Then, the gradient of the augmented cost function is derived. On this basis, we develop an effective computational method for solving the time-delay optimal control problem with continuous inequality constraints on the state and control via solving a sequence of approximate optimization problems, each of which can be solved as a nonlinear optimization problem by using existing gradient-based optimization techniques. This proposed method is then used to solve a practical optimal control problem arising in the study of a real evaporation process. The results obtained are highly satisfactory, showing that the proposed method is highly effective.The fourth problem that we consider is a max-min optimal control problem arising in the study of gradient elution chromatography, where the manipulative variables in the chromatographic process are to be chosen such that the separation efficiency is maximized. This problem has three non-standard characteristics: (i) The objective function is nonsmooth; (ii) each state variable is defined over a different time horizon; and (iii) the order of the final times for the state variable, the so-called retention times, are not fixed. To solve this problem, we first introduce a set of auxiliary decision variables to govern the ordering of the retention times. The integer constraints on these auxiliary decision variables are approximated by continuous boundedness constraints. Then, we approximate the control by a piecewise constant function, and apply a novel time-scaling transformation to map the retention times and control switching times to fixed points in a new time horizon. The retention times and control switching times become decision variables in the new time horizon. In addition, the max-min objective function is approximated by a minimization problem subject to an additional constraint. On this basis, the optimal control problem is reduced to an approximate nonlinear optimization problem subject to smooth constraints, which is then solved using a recently developed exact penalty function method. Numerical results obtained show that this approach is highly effective.Finally, some concluding remarks and suggestions for further study are made in the conclusion chapter.
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CARLOS, ERICA TELLES. "TRANSMISSION TARIFF ALLOCATION BASED ON NODAL METHOD AND MIN-MAX OPTIMIZATION TECHNIQUE." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=20533@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
A receita arrecadada pelo uso do sistema de transmissão é utilizada para cobrir custos de planejamento, operação e manutenção e deve ser paga por geradores e demandas, que são usuários do sistema. Um dos principais desafios é determinar a melhor maneira de alocar estes custos a geradores e demandas. Em países em desenvolvimento, como o Brasil, a acelerada expansão de geração e de transmissão, desencadeada por um crescimento acentuado de demanda, pode provocar significativa volatilidade e dispersão entre as tarifas dos usuários do sistema. Estes efeitos criam um ambiente inseguro para os investidores em geração. Para tratar este problema, esta dissertação propõe um novo método de alocação de custos pelo uso da transmissão que utiliza uma abordagem baseada na técnica de otimização min-max, e no método Nodal utilizado no Brasil. O propósito contido na utilização da técnica min-max é que os usuários com as piores tarifas devem ter prioridade em minimizá-las no processo de otimização. Assim, o objetivo é fornecer uma solução mais equitativa, e conseqüentemente, a redução de dispersão e volatilidade das tarifas ao longo do tempo, quando novos investimentos em geração e transmissão são feitos no sistema. Os resultados obtidos nos sistemas IEEE 24 barras e IEEE 118 barras indicam que a abordagem proposta fornece tarifas menos dispersas comparadas com outros métodos existentes, mas mantendo características desejáveis do método Nodal original. O método proposto também apresenta menos volatilidade nas tarifas no caso de mudanças (como diferentes despachos de geração) no sistema.
The revenue accrued for the use of the transmission system is used to recover the cost of planning, operation and maintenance and must be paid by generators and loads, which are the users of the system. One of the main challenges is how to establish the best way to allocate these costs to generators and loads. In developing countries, like Brazil, fast generation and transmission expansion triggered by a sharp demand growth, can cause significant volatility and dispersion among agents transmission tariffs. These effects can create an unsafe environment for new investors in generation. In order to face this problem, this dissertation proposes a new transmission cost allocation method that utilizes an approach based on the min-max optimization technique, and on the nodal method used in Brazil. The idea behind the utilization of min-max method is that the agents with the worst tariffs should have priority in the tariff optimization process. Thus, the objective is to provide an equitable solution and, consequently, a reduction of the dispersion and volatility of the tariffs over time, when new transmission or generation assets are incorporated into the system. The results presented for IEEE 24 bus and IEEE 118 bus systems indicate that the proposed approach gives less-dispersed tariffs compared with other existing methods, but keeping the desirable features of the traditional nodal method. The proposed method also shows less volatility in tariffs if changes (like different generation dispatches) are made to the system.
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SHIMODA, Masatoshi, Hideyuki AZEGAMI, and Toshiaki SAKURAI. "Numerical Solution for Min-Max Shape Optimization Problems (Minimum Design of Maximum Stress and Displacement)." 日本機械学会, 1998. http://hdl.handle.net/2237/12154.

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Chen, Xianjin. "Analysis and computation of multiple unstable solutions to nonlinear elliptic systems." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2990.

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Amrani-Benhalima, Faïza. "Problèmes de MIN-MAX en variables 0-1 : Algorithmes de résolution exacts et approchés." Valenciennes, 1997. https://ged.uphf.fr/nuxeo/site/esupversions/6fb2c7ce-df58-4bc6-bb55-a1a7c0529fcf.

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Le problème de Minmax en variables continues ou en variables entières a toujours suscité un intérêt croissant d'une part, parce que son champs d'application est vaste. Que ce soit dans le domaine des mathématiques, l'allocation de ressource, l'économie, l'aéronautique et même des jeux. D'autres part, parce que les problèmes traités sont classés en théorie de la complexité comme NP-difficile même quand il s'agit d'un problème de Minmax en variables 0-1 sans contrainte et avec seulement deux objectifs. Cette thèse contribue à l'étude des problèmes en variables bivalentes. Elle propose la résolution exacte et approchée des problèmes de Minmax ou Maxmin en variables 0-1 qui consistent à minimiser un objectif exprimé sous la forme d'un minimum ou maximum de plusieurs fonctions linéaires et soumis à un ensemble de contraintes.
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Lopez-Ibanez, Manuel. "Operational optimisation of water distribution networks." Thesis, Edinburgh Napier University, 2009. http://researchrepository.napier.ac.uk/Output/3044.

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Water distribution networks are a fundamental part of any modern city and their daily operations constitute a significant expenditure in terms of energy and maintenance costs. Careful scheduling of pump operations may lead to significant energy savings and prevent wear and tear. By means of computer simulation, an optimal schedule of pumps can be found by an optimisation algorithm. The subject of this thesis is the study of pump scheduling as an optimisation problem. New representations of pump schedules are investigated for restricting the number of potential schedules. Recombination and mutation operators are proposed, in order to use the new representations in evolutionary algorithms. These new representations are empirically compared to traditional representations using different network instances, one of them being a large and complex network from UK. By means of the new representations, the evolutionary algorithm developed during this thesis finds new best-known solutions for both networks. Pump scheduling as the multi-objective problem of minimising energy and maintenance costs in terms of Pareto optimality is also investigated in this thesis. Two alternative surrogate measures of maintenance cost are considered: the minimisation of the number of pump switches and the maximisation of the shortest idle time. A single run of the multi-objective evolutionary algorithm obtains pump schedules with lower electrical cost and lower number of pump switches than those found in the literature. Alternatively, schedules with very long idle times may be found with slightly higher electrical cost. Finally, ant colony optimisation is also adapted to the pump scheduling problem. Both Ant System and Max-Min Ant System are tested. Max-Min Ant System, in particular, outperforms all other algorithms in the large real-world network instance and obtains competitive results in the smallest test network. Computation time is further reduced by parallel simulation of pump schedules.
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下田, 昌利, Masatoshi Shimoda, 秀幸 畔上, Hideyuki Azegami, 俊明 桜井, and Toshiaki Sakurai. "形状最適化におけるミニマックス問題の数値解法(最大応力と最大変位の最小設計)." 日本機械学会, 1997. http://hdl.handle.net/2237/7249.

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Al-Hasani, Firas Ali Jawad. "Multiple Constant Multiplication Optimization Using Common Subexpression Elimination and Redundant Numbers." Thesis, University of Canterbury. Electrical and Computer Engineering, 2014. http://hdl.handle.net/10092/9054.

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The multiple constant multiplication (MCM) operation is a fundamental operation in digital signal processing (DSP) and digital image processing (DIP). Examples of the MCM are in finite impulse response (FIR) and infinite impulse response (IIR) filters, matrix multiplication, and transforms. The aim of this work is minimizing the complexity of the MCM operation using common subexpression elimination (CSE) technique and redundant number representations. The CSE technique searches and eliminates common digit patterns (subexpressions) among MCM coefficients. More common subexpressions can be found by representing the MCM coefficients using redundant number representations. A CSE algorithm is proposed that works on a type of redundant numbers called the zero-dominant set (ZDS). The ZDS is an extension over the representations of minimum number of non-zero digits called minimum Hamming weight (MHW). Using the ZDS improves CSE algorithms' performance as compared with using the MHW representations. The disadvantage of using the ZDS is it increases the possibility of overlapping patterns (digit collisions). In this case, one or more digits are shared between a number of patterns. Eliminating a pattern results in losing other patterns because of eliminating the common digits. A pattern preservation algorithm (PPA) is developed to resolve the overlapping patterns in the representations. A tree and graph encoders are proposed to generate a larger space of number representations. The algorithms generate redundant representations of a value for a given digit set, radix, and wordlength. The tree encoder is modified to search for common subexpressions simultaneously with generating of the representation tree. A complexity measure is proposed to compare between the subexpressions at each node. The algorithm terminates generating the rest of the representation tree when it finds subexpressions with maximum sharing. This reduces the search space while minimizes the hardware complexity. A combinatoric model of the MCM problem is proposed in this work. The model is obtained by enumerating all the possible solutions of the MCM that resemble a graph called the demand graph. Arc routing on this graph gives the solutions of the MCM problem. A similar arc routing is found in the capacitated arc routing such as the winter salting problem. Ant colony optimization (ACO) meta-heuristics is proposed to traverse the demand graph. The ACO is simulated on a PC using Python programming language. This is to verify the model correctness and the work of the ACO. A parallel simulation of the ACO is carried out on a multi-core super computer using C++ boost graph library.
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Gad, Mahmoud Attya Mohamed. "Optimalizační problémy při (max,min.)-lineárních omezeních a některé související úlohy." Doctoral thesis, 2015. http://www.nusl.cz/ntk/nusl-336972.

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Title: Optimization Problems under (max, min)-Linear Constraints and Some Related Topics. Author: Mahmoud Gad Department/Institue: Department of Probability and Mathematical Statis- tics Supervisor of the doctoral thesis: 1. Prof. RNDr. Karel Zimmermann,DrSc 2. Prof. Dr. Assem Tharwat, Cairo University, Egypt Abstract: Problems on algebraic structures, in which pairs of operations such as (max, +) or (max, min) replace addition and multiplication of the classical linear algebra have appeared in the literature approximately since the sixties of the last century. The first publications on these algebraic structures ap- peared by Shimbel [37] who applied these ideas to communication networks, Cunninghame-Green [12, 13], Vorobjov [40] and Gidffer [18] applied these alge- braic structures to problems of machine-time scheduling. A systematic theory of such algebraic structures was published probable for the first time in [14]. In recently appeared book [4] the readers can find latest results concerning theory and algorithms for (max, +)-linear systems of equations and inequalities. Since operation max replacing addition in no more a group, but a semigroup oppera- tion, it is a substantial difference between solving systems with variables on one side and systems with variables occuring on both sides of the equations....
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Book chapters on the topic "Min-max methods"

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Packel, Ed, and Stan Wagon. "Max-Min Methods: Mind Meets Machine." In Animating Calculus, 61–75. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-2408-2_7.

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Marques, Fernando C., and André Neves. "Applications of Min–Max Methods to Geometry." In Geometric Analysis, 41–77. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-53725-8_2.

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Ogryczak, Włodzimierz, and Tomasz Śliwiński. "On Direct Methods for Lexicographic Min-Max Optimization." In Computational Science and Its Applications - ICCSA 2006, 802–11. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11751595_85.

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Esparza, Javier, Thomas Gawlitza, Stefan Kiefer, and Helmut Seidl. "Approximative Methods for Monotone Systems of Min-Max-Polynomial Equations." In Automata, Languages and Programming, 698–710. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-70575-8_57.

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Ahlswede, Rudolf. "Classical Work: Edge-Disjoint Branchings, Min-Max Theorems, and Shortest Connection Networks." In Probabilistic Methods and Distributed Information, 413–33. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00312-8_20.

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Ţigan, Ştefan, Ion M. Stancu-Minasian, and Iliana Ţigan. "Specific Numerical Methods for Solving Some Special Max-min Programming Problems Involving Generalized Convex Functions." In Lecture Notes in Economics and Mathematical Systems, 395–410. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56645-5_28.

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Shimizu, Kiyotaka. "Multi-Objective Optimization Method by Satisfaction and Min-Max." In Lecture Notes in Economics and Mathematical Systems, 123–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-46607-6_14.

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Pycko, Sławomir. "An Indirect Incremental Method for Shakedown Analysis Based on the Min-Max Approach." In Inelastic Behaviour of Structures under Variable Loads, 381–98. Dordrecht: Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0271-1_21.

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Coello Coello, Carlos A. "Using the Min-Max Method to Solve Multiobjective Optimization Problems with Genetic Algorithms." In Lecture Notes in Computer Science, 303–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998. http://dx.doi.org/10.1007/3-540-49795-1_27.

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Cevher, Volkan, Georgios Piliouras, Ryann Sim, and Stratis Skoulakis. "Min-Max Optimization Made Simple: Approximating the Proximal Point Method via Contraction Maps." In Symposium on Simplicity in Algorithms (SOSA), 192–206. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2023. http://dx.doi.org/10.1137/1.9781611977585.ch18.

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Conference papers on the topic "Min-max methods"

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Bhatt, Sujay, Siuli Mukhopadhyay, Ameer Mulla, and Debraj Chakraborty. "Semidefinite programming methods for min-max robust parameter design." In 2012 International Conference on Statistics in Science, Business and Engineering (ICSSBE2012). IEEE, 2012. http://dx.doi.org/10.1109/icssbe.2012.6396614.

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Xie, Xiao-Min, and Yun Li. "Bisecting data partitioning methods for Min-Max Modular Support Vector Machine." In 2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2011). IEEE, 2011. http://dx.doi.org/10.1109/fskd.2011.6019750.

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Lazar, M., D. Munoz de la Pena, W. P. M. H. Heemels, and T. Alamo. "New Methods for Computing the Terminal Cost for Min-max Model Predictive Control." In 2007 American Control Conference. IEEE, 2007. http://dx.doi.org/10.1109/acc.2007.4282648.

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Barazandeh, Babak, Davoud Ataee Tarzanagh, and George Michailidis. "Solving a Class of Non-Convex Min-Max Games Using Adaptive Momentum Methods." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9414476.

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Kheriji, Amira, Faouzi Bouani, and Mekki Ksouri. "GGP approach to solve non convex min-max robust model predictive controller for a class of constrained MIMO systems." In 2010 XIth International Workshop on Symbolic and Numerical Methods, Modeling and Applications to Circuit Design (SM2ACD). IEEE, 2010. http://dx.doi.org/10.1109/sm2acd.2010.5672350.

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Damsgaard, Michael, John Rasmussen, and Søren T. Christensen. "Inverse Dynamics of Musculo-Skeletal Systems Using an Efficient Min/Max Muscle Recruitment Model." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/vib-21347.

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Abstract This paper presents an efficient criterion for solving the redundancy of the muscle recruitment problem in inverse dynamics of musculo-skeletal systems. It is a minimum fatigue criterion that is formulated as a min/max optimization problem. The criterion is briefly reviewed in comparison to other criteria and its implementation for large and complex system, such as the human body, is explained in detail. The optimization problem is solved numerically by means of linear programming, providing a very efficient, final algorithm. It is shown that special care must be taken of systems with groups of sub-maximally loaded muscles and methods to deal with this automatically are presented. The algorithms are implemented into a software system called AnyBody, and examples involving up to 100 muscles are demonstrated. Even models of this size are solved in fractions of a second for a single time step on a standard PC.
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Abachizadeh, Mahdi, Aghil Yousefi-Koma, and Masoud Shariatpanahi. "Optimization of a Beam-Type IPMC Actuator Using Insects Swarm Intelligence Methods." In ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2010. http://dx.doi.org/10.1115/esda2010-24840.

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In this paper, employing developed models of Ionic polymer metal composites, a cantilever beam made of Nafion is optimized for maximum tip deflection as well as maximum blocking (tip) force using the Min-Max method in a multi-objective discipline. Regarding the optimization procedure, saturation level of hydration, length and thickness of the beam, and applied voltage are considered as design variables. The robust and novel methods of continuous ant colony optimization (ACOR) and artificial bee colony (ABC), both inspired from collective behavior of ant and bee swarms, are here employed to guarantee finding near-optimal solutions in a continuous nonlinear constrained optimization schedule. Results obtained from several independent runs clearly demonstrate fast convergence with nearly identical results for both methods, conservatively claimed as global optima. In addition, it is shown that the multi-objective approach has ended in a reasonable reduction of tip deflection for a remarkable increase in blocking force.
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Xu, Ying, and Ajay Joneja. "A New Constrained Shape Deformation Operator With Applications in Footwear Design." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49833.

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In this paper, we address a problem that arises in several engineering applications: the deformation of a curve with constraints on its length. Since length is an integral property, typically computed by numerical methods, therefore implementing such shape change operations is non trivial. Recently some researchers have attempted to solve such problems for multi-resolution representations of curves. However, we take a differential geometric approach. The modification problem is formulated as constrained optimization problem, which is subsequently converted to an unconstrained min-max problem using Lagrangian multipliers. This problem is solved using the Uzawa method. The approach is implemented in MATLAB™, and some examples are presented in the paper.
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Keršič, Vid. "Interactive Evolutionary Computation Approach to Permutation Flow Shop Scheduling Problem." In 7th Student Computer Science Research Conference. University of Maribor Press, 2021. http://dx.doi.org/10.18690/978-961-286-516-0.8.

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Artificial intelligence and its subfields have be-come part of our everyday lives and eÿciently solve many problems that are very hard for us humans. But in some tasks, these methods strug-gle, while we, humans, are much better solvers with our intuition. Because of that, the ques-tion arises: why not combine intelligent methods with human skills and intuition? This paper pro-poses an Interactive Evolutionary Computation approach to the Permutation Flow Shop Schedul-ing Problem by incorporating human-in-the-loop in MAX-MIN Ant System through gamification of the problem. The analysis shows that combin-ing the evolutionary computation approach and human-in-the-loop leads to better solutions, sig-nificantly when the complexity of the problem in-creases.
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Dam, Nhan, Quan Hoang, Trung Le, Tu Dinh Nguyen, Hung Bui, and Dinh Phung. "Three-Player Wasserstein GAN via Amortised Duality." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/305.

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We propose a new formulation for learning generative adversarial networks (GANs) using optimal transport cost (the general form of Wasserstein distance) as the objective criterion to measure the dissimilarity between target distribution and learned distribution. Our formulation is based on the general form of the Kantorovich duality which is applicable to optimal transport with a wide range of cost functions that are not necessarily metric. To make optimising this duality form amenable to gradient-based methods, we employ a function that acts as an amortised optimiser for the innermost optimisation problem. Interestingly, the amortised optimiser can be viewed as a mover since it strategically shifts around data points. The resulting formulation is a sequential min-max-min game with 3 players: the generator, the critic, and the mover where the new player, the mover, attempts to fool the critic by shifting the data around. Despite involving three players, we demonstrate that our proposed formulation can be trained reasonably effectively via a simple alternative gradient learning strategy. Compared with the existing Lipschitz-constrained formulations of Wasserstein GAN on CIFAR-10, our model yields significantly better diversity scores than weight clipping and comparable performance to gradient penalty method.
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Reports on the topic "Min-max methods"

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Ding, Xu, Gary L. Cloud, and Basavaraju B. Raju. Noise Tolerance of Improved Max-min Scanning Method for Phase Determination. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada607290.

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Knupp, Patrick Michael, and David Minot Day. Incorporating the min-max mesh optimization method within the Target-Matrix Paradigm. Office of Scientific and Technical Information (OSTI), November 2012. http://dx.doi.org/10.2172/1055904.

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Derbentsev, V., A. Ganchuk, and Володимир Миколайович Соловйов. Cross correlations and multifractal properties of Ukraine stock market. Politecnico di Torino, 2006. http://dx.doi.org/10.31812/0564/1117.

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Recently the statistical characterizations of financial markets based on physics concepts and methods attract considerable attentions. The correlation matrix formalism and concept of multifractality are used to study temporal aspects of the Ukraine Stock Market evolution. Random matrix theory (RMT) is carried out using daily returns of 431 stocks extracted from database time series of prices the First Stock Trade System index (www.kinto.com) for the ten-year period 1997-2006. We find that a majority of the eigenvalues of C fall within the RMT bounds for the eigenvalues of random correlation matrices. We test the eigenvalues of C within the RMT bound for universal properties of random matrices and find good agreement with the results for the Gaussian orthogonal ensemble of random matrices—implying a large degree of randomness in the measured cross-correlation coefficients. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the eigenvalues outside the RMT bound display systematic deviations from the RMT prediction. We analyze the components of the deviating eigenvectors and find that the largest eigenvalue corresponds to an influence common to all stocks. Our analysis of the remaining deviating eigenvectors shows distinct groups, whose identities correspond to conventionally identified business sectors. Comparison with the Mantegna minimum spanning trees method gives a satisfactory consent. The found out the pseudoeffects related to the artificial unchanging areas of price series come into question We used two possible procedures of analyzing multifractal properties of a time series. The first one uses the continuous wavelet transform and extracts scaling exponents from the wavelet transform amplitudes over all scales. The second method is the multifractal version of the detrended fluctuation analysis method (MF-DFA). The multifractality of a time series we analysed by means of the difference of values singularity stregth (or Holder exponent) ®max and ®min as a suitable way to characterise multifractality. Singularity spectrum calculated from daily returns using a sliding 250 day time window in discrete steps of 1. . . 10 days. We discovered that changes in the multifractal spectrum display distinctive pattern around significant “drawdowns”. Finally, we discuss applications to the construction of crushes precursors at the financial markets.
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