Domenico Salvagnin – författare

Primal heuristics guarantee that feasible, high-quality solutions are provided at an early stage of the solving process, and thus are essential to the success of mixed-integer programming (MIP). By helping prove optimality faster, they allow MIP technology to extend to a wide variety of applications in discrete optimization. This first comprehensive guide to the development and use of primal heuristics within MIP technology and solvers is ideal for computational mathematics graduate students and industry practitioners. Through a unified viewpoint, it gives a unique perspective on how state-of-the-art results are integrated within the branch-and-bound approach at the core of the MIP technology. It accomplishes this by highlighting all the required knowledge needed to push the heuristic side of MIP solvers to their limit and pointing out what is left to do to improve them, thus presenting heuristic approaches for MIP as part of the MIP solving process.

Primal heuristics guarantee that feasible, high-quality solutions are provided at an early stage of the solving process, and thus are essential to the success of mixed-integer programming (MIP). By helping prove optimality faster, they allow MIP technology to extend to a wide variety of applications in discrete optimization. This first comprehensive guide to the development and use of primal heuristics within MIP technology and solvers is ideal for computational mathematics graduate students and industry practitioners. Through a unified viewpoint, it gives a unique perspective on how state-of-the-art results are integrated within the branch-and-bound approach at the core of the MIP technology. It accomplishes this by highlighting all the required knowledge needed to push the heuristic side of MIP solvers to their limit and pointing out what is left to do to improve them, thus presenting heuristic approaches for MIP as part of the MIP solving process.

This book constitutes the refereed proceedings of the 27th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2026, held in Padova, Italy, during June 17-19, 2026. The 33 full papers included in this book were carefully reviewed and selected from 113 submissions. The IPCO conference is held under the auspices of the Mathematical OptimizationSociety. It brings together researchers and practitioners working on a broad range of topics in integer programming and combinatorial optimization, and has become a premier forum for presenting recent advances in theory, computation, and applications.

This book constitutes the refereed proceedings of the 27th International Conference on Integer Programming and Combinatorial Optimization, IPCO 2026, held in Padova, Italy, during June 17-19, 2026. The 33 full papers included in this book were carefully reviewed and selected from 113 submissions. The IPCO conference is held under the auspices of the Mathematical OptimizationSociety. It brings together researchers and practitioners working on a broad range of topics in integer programming and combinatorial optimization, and has become a premier forum for presenting recent advances in theory, computation, and applications.

This book constitutes the proceedings of the 14th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming for Combinatorial Optimization Problems, CPAIOR 2017, held in Padua, Italy, in June 2017. The 32 full papers presented together with 6 abstracts were carefully reviewed and selected from numerous submissions. The conference brings together interested researchers from constraint programming, artificial intelligence, and operations research to present new techniques or applications in the intersection of these fields and provides an opportunity for researchers in one area to learn about techniques in the others, and to show how the integration of techniques from different fields can lead to interesting results on large and complex problems.