Exact exponential algorithms / (Record no. 91518)
[ view plain ]
| 000 -LEADER | |
|---|---|
| fixed length control field | 01876 a2200205 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240207b2010 |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783642265662 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 511.352 FOM-F |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Fomin, Fedor V. |
| 245 ## - TITLE STATEMENT | |
| Title | Exact exponential algorithms / |
| Statement of responsibility, etc. | Fedor V. Fomin and Dieter Kratsch |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Place of publication, distribution, etc. | Germany |
| Name of publisher, distributor, etc. | Springer |
| Date of publication, distribution, etc. | 2010 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 203 p. |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE | |
| Title | Texts in Theoretical Computer Science. |
| 500 ## - GENERAL NOTE | |
| General note | For a long time, computer scientists have distinguished between fast and slow algorithms. Fast (or good) algorithms are the algorithms that run in polynomial time, which means that the number of steps required for the algorithm to solve a problem is bounded by some polynomial in the length of the input. All other algorithms are slow (or bad). The running time of slow algorithms is usually exponential. This book is about bad algorithms. There are several reasons why we are interested in exponential time algorithms. Most of us believe that many natural problems cannot be solved by polynomial time algorithms. The most famous and oldest family of hard problems is the family of NP-complete problems. Most likely no polynomial-time algorithms are solving these hard problems and in the worst-case scenario, the exponential running time is unavoidable. Every combinatorial problem is solvable in? nite time by enumerating all possible solutions, i. e. by brute force search. But is brute force search always unavoidable? Not. Already in the nineteen sixties and 1970s, it was known that some NP-complete problems could be solved significantly faster than by brute force search. Three classic examples are the following algorithms for the TRAVELLING SALESMAN problem, MAXIMUM INDEPENDENT SET, and COLORING. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Algorithms |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer algorithms |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Kratsch, Dieter |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| Withdrawn status | |
| Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Current library | Shelving location | Date acquired | Total Checkouts | Full call number | Barcode | Date last seen | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | 510 | BITS Pilani Hyderabad | Text & Reference Section (Student cannot borrow these books) | 17/01/2024 | 511.352 FOM-F | 48157 | 13/07/2024 | Course Reference Books |