| Optimization under Composite Monotonic Constraints and Constrained Optimization over the Efficient Set | p. 3 |
| Introduction | p. 3 |
| Some basic concepts and results of monotonic optimization | p. 5 |
| Problems with composite monotonic constraints | p. 7 |
| Constrained optimization over the efficient set | p. 11 |
| Solution method for problem (Q) | p. 15 |
| Improvements for problems (OWE) and (OE) | p. 19 |
| Problems with a composite monotonic objective function | p. 25 |
| Illustrative examples and computational results | p. 26 |
| References | p. 29 |
| On a Local Search for Reverse Convex Problems | p. 33 |
| Introduction | p. 33 |
| Some features of RCP | p. 34 |
| Local search methods | p. 36 |
| Computational testing | p. 40 |
| Conclusion | p. 42 |
| References | p. 42 |
| Some Transformation Techniques in Global Optimization | p. 45 |
| Introduction | p. 45 |
| The MINLP Problem | p. 46 |
| The transformation approach | p. 47 |
| Examples of transformations | p. 52 |
| The GGPECP algorithm | p. 55 |
| Convergence to the globally optimal solution | p. 57 |
| A numerical example | p. 59 |
| Some aspects on the numerical solution approach | p. 64 |
| Conclusions | p. 70 |
| References | p. 71 |
| Solving Nonlinear Mixed Integer Stochastic Problems: a Global Perspective | p. 75 |
| Introduction | p. 76 |
| Motivations | p. 76 |
| SMINLP: state of the art | p. 77 |
| Problem formulation | p. 84 |
| The two-phase solution approach | p. 86 |
| Illustrative application: the Stochastic Trim Loss Problem | p. 98 |
| Concluding Remarks | p. 104 |
| References | p. 106 |
| Application of Quasi Monte Carlo Methods in Global Optimization | p. 111 |
| Introduction | p. 111 |
| Analysis of Quasirandom Search methods | p. 114 |
| Single linkage and multilevel single linkage methods | p. 117 |
| Computational experiments | p. 120 |
| Conclusion | p. 131 |
| References | p. 131 |
| GLOB - A new VNS-based Software for Global Optimization | p. 135 |
| Introduction | p. 135 |
| VNS methodology | p. 136 |
| Software package GLOB | p. 137 |
| Numerical experiments | p. 141 |
| Conclusion | p. 147 |
| References | p. 148 |
| Disciplined Convex Programming | p. 155 |
| Introduction | p. 155 |
| Motivation | p. 156 |
| Convex programming | p. 162 |
| Modeling frameworks | p. 169 |
| Disciplined convex programming | p. 171 |
| The convexity ruleset | p. 172 |
| The atom library | p. 183 |
| Verification | p. 188 |
| Creating disciplined convex programs | p. 191 |
| Implementing atoms | p. 193 |
| Conclusion | p. 199 |
| References | p. 200 |
| Writing Global Optimization Software | p. 211 |
| Introduction | p. 211 |
| Global Optimization algorithms | p. 214 |
| Global Optimization software | p. 223 |
| Optimization software framework design | p. 232 |
| Symbolic manipulation of mathematical expressions | p. 240 |
| Local solvers | p. 247 |
| Global solvers | p. 248 |
| Conclusion | p. 257 |
| References | p. 258 |
| MathOptimizer Professional: Key Features and Illustrative Applications | p. 263 |
| Introduction | p. 263 |
| Global Optimization | p. 266 |
| LGO Solver Suite | p. 267 |
| MathOptimizer Professional | p. 268 |
| Illustrative applications: solving sphere packing models | p. 271 |
| Conclusions | p. 276 |
| References | p. 277 |
| Variable Neighborhood Search for Extremal Graphs 14: The AutoGraphiX 2 System | p. 281 |
| Introduction | p. 281 |
| AGX 2 Interactive functions | p. 283 |
| Algebraic syntax used in AutoGraphiX | p. 291 |
| Optimization using Variable Neighborhood Search | p. 294 |
| AutoGraphiX Tasks | p. 299 |
| Automated proofs | p. 301 |
| Some examples | p. 305 |
| Conclusion | p. 308 |
| References | p. 308 |
| From Theory to Implementation: Applying Metaheuristics | p. 311 |
| Introduction | p. 311 |
| Class hierarchy | p. 316 |
| Implementation: The p-Median Problem | p. 333 |
| Conclusions | p. 338 |
| References | p. 339 |
| ooMILP - AC++ Callable Object-oriented Library and the Implementation of its Parallel Version using CORBA | p. 353 |
| Introduction | p. 353 |
| ooMILP Overview | p. 356 |
| C++ objects and pre-CORBA serial implementation | p. 357 |
| Initial CORBA Version | p. 361 |
| Partially decomposable MILPs | p. 366 |
| Parallel solution software architecture | p. 368 |
| Conclusions | p. 375 |
| References | p. 375 |
| Global Order-Value Optimization by means of a Multistart Harmonic Oscillator Tunneling Strategy | p. 379 |
| Introduction | p. 379 |
| Local algorithm | p. 381 |
| Lissajous motions | p. 382 |
| Global algorithm | p. 384 |
| Hidden patterns | p. 387 |
| Numerical experiments | p. 388 |
| Conclusions | p. 394 |
| References | p. 397 |
| On generating Instances for the Molecular Distance Geometry Problem | p. 405 |
| Introduction | p. 405 |
| Moré-Wu instances | p. 406 |
| New instances | p. 407 |
| Conclusion | p. 413 |
| References | p. 414 |
| Index | p. 415 |
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