Linear programming
A powerful tool in the field of mathematics, linear programming focuses on maximizing or minimizing a linear objective function, subject to linear equality and inequality constraints. Ideal for students, professionals, and researchers, this category encompasses a variety of texts that explore theoretical foundations as well as practical applications across diverse disciplines. Whether for academic growth or real-world problem-solving, resources in this category offer essential insights into optimization techniques and strategies.
Convex Optimization
Stephen Boyd, Lieven Vandenberghe
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Smoothings of Piecewise Linear Manifolds
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Linear Programming and Extensions
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Approaches to the Theory of Optimization
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Mathematical Programs with Equilibrium Constraints
Jong-Shi Pang, Zhi-Quan Luo, Daniel Ralph
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Linear Inequalities and Related Systems
Albert William Tucker, Harold W. Kuhn
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An Introduction to Linear Transformations in Hilbert Space
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Linear Operators and Linear Systems: An Analytical Approach to Control Theory
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Introduction to Linear Goal Programming
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PARTITIONS: OPTIMALITY & CLUSTERING (V19)
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Mathematical Programs with Equilibrium Constraints
Jong-Shi Pang, Zhi-Quan Luo, Daniel Ralph
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Introduction to Linear and Convex Programming
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Robust Optimization
Aharon Ben-Tal, Arkadi Nemirovski, Laurent El Ghaoui
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Robust Static Super-Replication of Barrier Options
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Stochastic Control and Mathematical Modeling
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Boolean Functions: Theory, Algorithms, and Applications
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CONTINUOUS & DISCONTINUOUS PIECEWISE-SMOOTH ONE-DIMEN MAPS
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Networks: Optimisation and Evolution
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![CHAOS, CNN, MEMRISTORS AND BEYOND [DVD]: CNN](https://www.patogupirkti.lt/media/catalogen/product/978981/9789814434799.jpg)
CHAOS, CNN, MEMRISTORS AND BEYOND [DVD]: CNN
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Stochastic Scheduling: Expectation-Variance Analysis of a Schedule
Lingrui Liao, Balaji Nagarajan, Subhash C. Sarin
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Optimization Models
Giuseppe C. Calafiore, Laurent El Ghaoui
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Convex Optimization of Power Systems
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An Introduction to Nonlinear Optimization Theory
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Proceedings of the Princeton Symposium on Mathematical Programming
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Category „Linear programming“
Linear programming is a powerful technique utilized in various fields, including economics, engineering, and operations research. This mathematical method helps in optimizing a particular outcome, whether it be maximizing profit, minimizing cost, or achieving the best efficiency. Students, professionals, and enthusiasts who wish to delve deeper into this analytical approach will find a wide array of resources available in this category.
The roots of linear programming trace back to the 1940s when it emerged out of wartime logistics challenges. Since then, it has evolved into a fundamental aspect of quantitative decision-making, supported by numerous theories and applications. Readers interested in the underlying concepts, algorithms, and practical applications will find comprehensive texts that explore linear inequalities, simplex methods, and dual problems, providing a solid grounding for both novice learners and seasoned practitioners.
Books in this category not only cover the theoretical foundations of linear programming but also present real-world scenarios and case studies that showcase its relevance in diverse disciplines, from transportation and manufacturing to finance and resource allocation. Authors who specialize in this field often bring forth innovative insights and problem-solving techniques that can significantly enhance understanding and application.
By exploring the resources available within the linear programming category, readers can gain the skills necessary to tackle complex optimization problems. Each book offers a unique perspective, ensuring that there's something to suit every learner's style and needs, making it an invaluable asset for anyone looking to harness the power of optimization in their work or studies.