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International Series in Operations Research & Management ScienceVolume Series Editor Frederick S. Hillier Stanfo.
Table of contents
- Numerical solution of a general interval quadratic programming model for portfolio selection
- Learn how to quickly solve optimization problems with linear programming in Python
- Optimization for decision making: Linear and quadratic models
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Data Analytics. Thomas A. Mathematics for Engineers. Georges Fiche. Markov Processes for Stochastic Modeling. Oliver Ibe. Simulation and the Monte Carlo Method. Reuven Y. Introduction to Applied Linear Algebra. Stephen Boyd. Fundamentals of Stochastic Networks. Oliver C. Economic Foundations of Symmetric Programming. Quirino Paris.
Data Mining and Analysis. Mohammed J.
Carol Ptak. Probabilistic Composition of Preferences, Theory and Applications. Annibal Parracho Sant'Anna.
Numerical solution of a general interval quadratic programming model for portfolio selection
Michael L. Machine Learning Refined. Jeremy Watt. Product Lifecycle Management. John Stark. Design Science Research. Aline Dresch. Partially Observed Markov Decision Processes. Vikram Krishnamurthy. Managing Complex, High Risk Projects. Franck Marle.
Optimal Control. Frank L. Predictive Control for Linear and Hybrid Systems. Francesco Borrelli. Planning Production and Inventories in the Extended Enterprise. Karl G Kempf. Handbook of Ocean Container Transport Logistics. Chung-Yee Lee. Applied Digital Signal Processing. Dimitris G. Numerical Analysis and Optimization. Mehiddin Al-Baali. Product Lifecycle Management Volume 2.
Learn how to quickly solve optimization problems with linear programming in Python
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Optimization for decision making: Linear and quadratic models
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