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Branch and Bound Methods for Combinatorial Problems
Unlock a practical framework for solving difficult optimization problems.
This book introduces the branch and bound method and shows how it partitions large solution spaces into manageable pieces, then uses bounds to prune non-promising options.
Through concrete examples, including the traveling salesman problem and scheduling scenarios, you’ll see how lower bounds, branching decisions, and problem structure work together to find optimal solutions. The discussion blends theory with hands-on technique, illustrating why some strategies succeed where others fail and how memory can accelerate search.
Understand how to create and use lower bounds to guide the search for optimal solutions. Learn practical branching rules and how to handle constraints to eliminate infeasible options. See how reductions and problem structure turn large problems into sequences of simpler subproblems. Explore applications from scheduling and flow shops to coordinating complex networks. Ideal for readers of operations research and combinatorial optimization seeking clear methods and real‑world examples.
This book introduces the branch and bound method and shows how it partitions large solution spaces into manageable pieces, then uses bounds to prune non-promising options.
Through concrete examples, including the traveling salesman problem and scheduling scenarios, you’ll see how lower bounds, branching decisions, and problem structure work together to find optimal solutions. The discussion blends theory with hands-on technique, illustrating why some strategies succeed where others fail and how memory can accelerate search.
Understand how to create and use lower bounds to guide the search for optimal solutions. Learn practical branching rules and how to handle constraints to eliminate infeasible options. See how reductions and problem structure turn large problems into sequences of simpler subproblems. Explore applications from scheduling and flow shops to coordinating complex networks. Ideal for readers of operations research and combinatorial optimization seeking clear methods and real‑world examples.
57 pages, Hardcover
Published August 24, 2018
About the author
John D.C. Little
41 books1 followerJohn Dutton Conant Little was an Institute Professor at the Massachusetts Institute of Technology best known for his result in operations research, Little's law.
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