

Linear and Nonlinear Programming by David G Luenberger
The 5th edition of this classic textbook covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve that problem. End-of-chapter exercises are provided for all chapters. The material is organized into three separate parts. Part I offers a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. In turn, Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. As such, Parts II and III can easily be used without reading Part I and, in fact, the book has been used in this way at many universities. New to this edition are popular topics in data science and machine learning, such as the Markov Decision Process, Farkas’ lemma, convergence speed analysis, duality theories and applications, various first-order methods, stochastic gradient method, mirror-descent method, Frank-Wolf method, ALM/ADMM method, interior trust-region method for non-convex optimization, distributionally robust optimization, online linear programming, semidefinite programming for sensor-network localization, and infeasibility detection for nonlinear optimization.-
Designing Competitive Electricity Markets
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Principles of Forecasting
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Optimal Search for Moving Targets
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An Introduction to Robust Combinatorial Optimization
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Handbook of Markov Decision Processes
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Computational Probability
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Handbook of Stochastic Models and Analysis of Manufacturing System Operations
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Modeling Uncertainty
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Analysis and Modeling of Manufacturing Systems
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Military Operations Research
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Stochastic Benchmarking
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Constraint-Based Scheduling
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Quantitative Models for Supply Chain Management
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Health Care Benchmarking and Performance Evaluation
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Elicitation
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Linear Programming
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Markovian Demand Inventory Models
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Building Supply Chain Excellence in Emerging Economies
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Evaluation and Decision Models
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Mathematical Programming and Financial Objectives for Scheduling Projects
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Judgment in Predictive Analytics
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Fundamentals of Traffic Simulation
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Benchmarking with DEA, SFA, and R
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Outline of Complex Systems Management Theory— Based on Irreversibility of Reductionism Thinking
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Handbook of Semidefinite Programming
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Quantitative Risk Analysis of Air Pollution Health Effects
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Robust Optimization in Electric Energy Systems
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Making Better Decisions
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The Theory and Practice of Revenue Management
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Multicriteria Decision Making
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Optimal Inventory Modeling of Systems
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Queueing Networks
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Handbook on Data Envelopment Analysis
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Process Optimization
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Spare Parts Inventory Control under System Availability Constraints
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Applied Linear Regression for Business Analytics with R
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Economics of Power Systems
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Handbook of Quantitative Supply Chain Analysis
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Multicriterion Decision in Management
| SKU | Unavailable |
| ISBN 13 | |
| ISBN 10 | |
| Title | Linear and Nonlinear Programming |
| Author | David G Luenberger |
| Series | |
| Condition | Unavailable |
| Binding Type | |
| Publisher | |
| Year published | |
| Number of pages | |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |
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