Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research. This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages. This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.MIT, Cambridge, pp 316a330 15. Cheadle AM, Harvey ... Cheng BMW, Lee JHM, Wu JCK (1996) Speeding up constraint propagation by redundant modeling. In: Freuder EC ... Paris 23. van Hoeve WJ, Pesant G, Rousseau LM, Sabharwal A ( 2006) Revisiting the sequence constraint. In: Benhamou F ... Hooker JN (2009) A principled approach to mixed integer/linear problem formulation. In: Chinneck JW anbsp;...
|Author||:||Pascal van Hentenryck, Michela Milano|
|Publisher||:||Springer Science & Business Media - 2010-11-05|