## Combinatorial and Global OptimizationCombinatorial 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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### Contents

A Hybrid Scatter Genetic Tabu Approach for Continuous Global | 11 |

Exact Rates of Prokhorov Convergence under Three Moment Condi | 33 |

Algorithms for the Consistency Analysis in Scenario Projects | 55 |

Assignment of Reusable and NonReusable Frequencies | 75 |

Image Space Analysis for Vector Optimization and Variational Inequal | 97 |

Solving Quadratic Knapsack Problems by Reformulation and Tabu | 111 |

A A Groenwold and J A Snyman | 124 |

On Pareto Efficiency A General Constructive Existence Principle | 133 |

example | 186 |

Heuristic Solutions of Vehicle Routing Problems in Supply Chain Man | 205 |

A New Finite Cone Covering Algorithm for Concave Minimization | 237 |

A Diagonal Global Optimization Method | 251 |

Frequency Assignment for Very Large Sparse Networks | 265 |

A Derivative Free Minimization Method for Noisy Functions | 283 |

Tight QAP Bounds via Linear Programming | 297 |

An Application of the Simulated Annealing | 305 |

Kim and P M Pardalos | 146 |

Semidefinite Programming Approaches for MAX2SAT and MAX3 | 161 |

On a Data Structure in a Global Description of Sequences | 177 |

ImpactEcho Experiments317 | 317 |

Normal Branch and Bound Algorithms for General Nonconvex Quadratic | 333 |

### Other editions - View all

Combinatorial and Global Optimization Panos M Pardalos,Athanasios Migdalas,Rainer E Burkard Limited preview - 2002 |

### Common terms and phrases

2002 World Scientific AFA1 AFA2 applications approximation assignment problem BB algorithm branch and bound Burkard cliques Combinatorial and Global Combinatorial Optimization competitive ratio computational concave cone considered constraints construction convergence convex corresponding crack defined denote distance dual feasible efficient exists extreme points F(xn facility FCNFP formulation frequency assignment genetic algorithms geometric given Global Optimization graph coloring Hamiltonian cycle Hamiltonian path HC-set Hence heuristic inequalities instances integer patterns integer relations inter-clique edges iteration key factors Lemma locations lower bound Math Mathematics Migdalas minimization minimum neighborhood normal objective function obtained on-line algorithm Operations Research optimal solution optimization problem P.M. Pardalos PLNFP polynomial primal procedure Proof Proposition quadratic radio coloring radio labelling random satisfying scalar SDP relaxation sequence sequential Simulated Annealing solve span Step structural numbers tabu search technique Theorem tour traveling salesman problem variables vehicle routing problem vertex vertices