All listings for this product
About this product
- DescriptionData Correcting Approaches in Combinatorial Optimization focuses on algorithmic applications of the well kwn polymially solvable special cases of computationally intractable problems. The purpose of this text is to design practically efficient algorithms for solving wide classes of combinatorial optimization problems. Researches, students and engineers will benefit from new bounds and branching rules in development efficient branch-and-bound type computational algorithms. This book examines applications for solving the Traveling Salesman Problem and its variations, Maximum Weight Independent Set Problem, Different Classes of Allocation and Cluster Analysis as well as some classes of Scheduling Problems. Data Correcting Algorithms in Combinatorial Optimization introduces the data correcting approach to algorithms which provide an answer to the following questions: how to construct a bound to the original intractable problem and find which element of the corrected instance one should branch such that the total size of search tree will be minimized. The PC time needed for solving intractable problems will be adjusted with the requirements for solving real world problems.
- Author(s)Boris Goldengorin,Panos M. Pardalos
- PublisherSpringer-Verlag New York Inc.
- Date of Publication11/10/2012
- SubjectComputing: Professional & Programming
- Series TitleSpringerBriefs in Optimization
- Place of PublicationNew York, NY
- Country of PublicationUnited States
- ImprintSpringer-Verlag New York Inc.
- Content Note41 black & white illustrations, 21 black & white tables, biography
- Weight188 g
- Width156 mm
- Height234 mm
- Spine6 mm
- Format DetailsTrade paperback (US)
Best-selling in Non-Fiction Books
Save on Non-Fiction Books
- AU $37.00Trending at AU $37.87
- AU $23.22Trending at AU $28.84
- AU $17.51Trending at AU $30.55
- AU $6.90Trending at AU $9.93
- AU $15.62Trending at AU $17.52
- AU $43.92Trending at AU $50.31
- AU $31.46Trending at AU $40.93
This item doesn't belong on this page.
Thanks, we'll look into this.