• Title Operations Research - the Art of Making Good Decisions
• Author(s) Kuodi Jian
• Publisher: InTech (December 28, 2016)
• Hardcover 140 pages
• eBook PDF files
• Language: English
• ISBN-10: N/A
• ISBN-13: 978-9535128175
• Share This:  

Book Description

This book is dedicated to operations research of broad applications, such as improving informational bases of performance measurement with grey relational analysis, application of lean methodologies in a neurosurgery high dependency unit, iteration algorithms in Markov decision processes with state-action-dependent discount factors and unbounded costs, financial feasibility analysis of Natura Rab business case study, and mathematical modeling of isothermal drying and its potential application in the design of the industrial drying regimes of clay products.

Operations research is an important topic. In addition to its obvious benefits of winning a war, making most profit in a business endeavor, and constructing a correct mathematical model, it also provides a tool for efficient use of natural resources. Furthermore, both theory and practice of operations research and its related concepts are covered in the book, and a reader can benefit from this balanced coverage.

• Dr. Kuodi Jian holds B.S. degree in Computer Science from the University of Mary Hardin-Baylor, and the M.S. degree in Computer Science and the Ph. D. degrees in Computer Science and Operations Research from the North Dakota State University.

• Amazon

• Operations Research (OR), Linear Programming, Optimization, Approximation, etc.
• Financial Mathematics and Mathematical Economics
• Algorithms and Data Structures
• Computational and Algorithmic Mathematics
• Computational Complexity

• Operations Research - the Art of Making Good Decisions (Kuodi Jian)
• PDF Format

• Algorithms for Decision Making (Mykel Kochenderfer, et al)

  This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.

• Convex Optimization for Machine Learning (Changho Suh)

  This book covers an introduction to convex optimization, one of the powerful and tractable optimization problems that can be efficiently solved on a computer. The goal is to help develop a sense of what convex optimization is, and how it can be used.

• Design of Heuristic Algorithms for Hard Optimization

  This open access book demonstrates all the steps required to design heuristic algorithms for difficult optimization. The classic problem of the travelling salesman is used as a common thread to illustrate all the techniques discussed.

• Algorithms for Optimization (Mykel J. Kochenderfer, et al.)

  A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems. Readers will learn about computational approaches for a range of challenges.

• Sine Cosine Algorithm for Optimization (Jagdish Bansal, et al.)

  This book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of Metaheuristics algorithms.

• Introduction to Online Convex Optimization (Elad Hazan)

  This book presents a robust machine learning approach that contains elements of mathematical optimization, game theory, and learning theory: an optimization method that learns from experience as more aspects of the problem are observed.

• Convex Optimization (Stephen Boyd, et al.)

  On recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

• Optimization for Decision Making: Linear and Quadratic Models

  This book illustrates how to formulate real world problems using linear and quadratic models; It focus on developing modeling skills to support valid decision making for complex real world problems.

• Global Optimization Algorithms - Theory and Application

  This book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems. It especially focuses on Evolutionary Computation by discussing evolutionary algorithms, genetic algorithms, Genetic Programming, etc.

• Inventory Analytics: A Practicable, Python-Driven Approach

  This book provides a comprehensive and accessible introduction to the theory and practice of Inventory Control - a significant research area central to supply chain planning. It adopts a practicable, Python-driven approach to illustrating theories and concepts.