
Combinatorial And Global Optimization
- 372 pages
- English
- PDF
- Available on iOS & Android
Combinatorial And Global Optimization
About this book
Combinatorial and global optimization problems appear in a wide range of applications in operations research, engineering, biological science, and computer science. In combinatorial optimization and graph theory, many approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic, and algebraic techniques. Such techniques include global optimization formulations, semidefinite programming, and spectral theory. Recent major successes based on these approaches include interior point algorithms for linear and discrete problems, the celebrated Goemans-Williamson relaxation of the maximum cut problem, and the Du-Hwang solution of the Gilbert-Pollak conjecture. Since integer constraints are equivalent to nonconvex constraints, the fundamental difference between classes of optimization problems is not between discrete and continuous problems but between convex and nonconvex optimization problems. This volume is a selection of refereed papers based on talks presented at a conference on "Combinatorial and Global Optimization" held at Crete, Greece.
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Table of contents
- Contents
- Preface
- A Forest Exterior Point Algorithm for Assignment Problems
- A Hybrid Scatter Genetic Tabu Approach for Continuous Global Optimization
- Exact Rates of Prokhorov Convergence under Three Moment Conditions
- Location/Allocation of Queuing Facilities in Continuous Space using Minisum and Minimax Criteria
- Algorithms for the Consistency Analysis in Scenario Projects
- Assignment of Reusable and Non-Reusable Frequencies
- Image Space Analysis for Vector Optimization and Variational Inequalities. Scalarization
- Solving Quadratic Knapsack Problems by Reformulation and Tabu Search. Single Constraint Case
- Global Optimization using Dynamic Search Trajectories
- On Pareto Efficiency. A General Constructive Existence Principle
- Piecewise Linear Network Flow Problems
- Semidefinite Programming Approaches for MAX-2-SAT and MAX-3-SAT: computational perspectives
- On a Data Structure in a Global Description of Sequences
- Heuristic Solutions of Vehicle Routing Problems in Supply Chain Management
- A New Finite Cone Covering Algorithm for Concave Minimization
- A Diagonal Global Optimization Method
- Frequency Assignment for Very Large Sparse Networks
- A Derivative Free Minimization Method for Noisy Functions
- Tight QAP Bounds via Linear Programming
- GPS Network Design: An Application of the Simulated Annealing Heuristic Technique
- Global Optimization for Crack Identification:Impact-Echo Experiments
- Normal Branch and Bound Algorithms for General Nonconvex Quadratic Programming