Home » Linear and Integer Optimization
Product Image

Linear and Integer Optimization

Gerard Sierksma | Yori Zwols
€132.99
Quantity:
In stock with our UK publisher. 14-28 days
Delivery/Collection within 10-20 working days
14 days return policy Shipping & Delivery
A01=Gerard Sierksma
A01=Yori Zwols
advanced optimization case studies
Author_Gerard Sierksma
Author_Yori Zwols
Category=PBUH
Category=UYA
Chap Te
combinatorial optimization
dynamic optimization strategies
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
Feasible Basic Solution
Hand Side Vector
Hyperplane H1
Initial Feasible Basic Solution
Knapsack Problem
mathematical programming
Minimum Cost Flow Problem
Mixed Integer Linear Optimization Model
Multiple Optimal Solutions
Network Simplex Algorithm
Node Arc Incidence Matrix
Nonbasic Variables
operations research methods
Optimal Dual Solution
Optimal Dual Values
Optimal Feasible Basic Solution
Optimal Objective
Optimal Vertex
Primal Decision Variable
sensitivity analysis techniques
Simplex Algorithm
Simplex Tableau
Slack Variables
Subtour Elimination Constraints
support vector machines
Totally Unimodular
Traveling Salesman Problem
Vertex V1

Product details

  • ISBN 9781498710169
  • Weight: 1430g
  • Dimensions: 178 x 254mm
  • Publication Date: 01 May 2015
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns
Description

Presenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig’s simplex algorithm, duality, sensitivity analysis, integer optimization models, and network models are introduced.

More advanced topics also are presented including interior point algorithms, the branch-and-bound algorithm, cutting planes, complexity, standard combinatorial optimization models, the assignment problem, minimum cost flow, and the maximum flow/minimum cut theorem.

The second part applies theory through real-world case studies. The authors discuss advanced techniques such as column generation, multiobjective optimization, dynamic optimization, machine learning (support vector machines), combinatorial optimization, approximation algorithms, and game theory.

Besides the fresh new layout and completely redesigned figures, this new edition incorporates modern examples and applications of linear optimization. The book now includes computer code in the form of models in the GNU Mathematical Programming Language (GMPL). The models and corresponding data files are available for download and can be readily solved using the provided online solver.

This new edition also contains appendices covering mathematical proofs, linear algebra, graph theory, convexity, and nonlinear optimization. All chapters contain extensive examples and exercises. This textbook is ideal for courses for advanced undergraduate and graduate students in various fields including mathematics, computer science, industrial engineering, operations research, and management science.
About Gerard Sierksma | Yori Zwols

Gerard Sierksma, PhD, University of Groningen, The Netherlands
Yori Zwols, PhD, Google UK, London

More from this author