Primal Heuristics in Integer Programming (Paperback)

Timo Berthold

ISBN 10: 1009574809 / ISBN 13: 9781009574808

Editore: Cambridge University Press, Cambridge, 2025

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Paperback. 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 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Codice articolo 9781009574808

Dati bibliografici

• Titolo: Primal Heuristics in Integer Programming (Paperback)
• Editore: Cambridge University Press, Cambridge
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 1009574809
• ISBN 13: 9781009574808
• Rilegatura: Paperback
• Condizione: new

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Riassunto

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.