Primal Heuristics in Integer Programming

Auteur
Timo Berthold is Lecturer at TU Berlin and a Director at FICO, leading the MIP research and development team of the FICO Xpress Solver. He is an expert on heuristic methods and computational mixed-integer linear and nonlinear programming. He has won multiple awards for his research. Andrea Lodi is Andrew H. and Ann R. Tisch Professor at the Jacobs Technion-Cornell Institute at Cornell Tech and the Technion. His main research interests are in mixed-integer linear and nonlinear programming and data science. He has been recognized by IBM and Google faculty awards, and the INFORMS Optimization Society 2021 Farkas Prize. He is a 2023 INFORMS Fellow.Domenico Salvagnin is Associate Professor in Operations Research at the University of Padua, Italy. He was lead development scientist in the IBM CPLEX team in 20152017 and is currently scientific consultant for FICO Xpress. His research interests include computational integer programming, constraint programming and hybrid methods for optimization.

Texte du rabat
Primal heuristics have allowed mixed-integer programming to extend to many practical applications by guaranteeing that feasible solutions of high quality are available at an early stage of the solving process. This first comprehensive book on its use and development is ideal for graduate students and industry practitioners.

Contenu

Introduction and concepts; 2. Large neighborhood search; 3. Rounding, propagation and diving; 4. The feasibility pump family; 5. Pivoting and line search heuristics; 6. Computational study; 7. Primal heuristics for mixed integer nonlinear programming; 8. Machine learning for primal heuristics; Appendix. Quiz solutions; References; Index.