appveyorimgbotreadme
Last change
on this file since 31694c8b58 was
8dcf4701e6,
checked in by Oleksii Serdiuk, 14 years ago
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Added deployment rules for Maemo 5 target. Untested.
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Property mode set to
100644
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File size:
5.8 KB
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Rev | Line | |
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[8dcf4701e6] | 1 | Source: tspsg |
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| 2 | Section: user/hidden |
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| 3 | Priority: optional |
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| 4 | Maintainer: Oleksii Serdiuk <[email protected]> |
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| 5 | Homepage: http://tspsg.info/ |
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| 6 | Standards-Version: 3.7.3 |
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| 7 | Build-Depends: debhelper (>= 5), libqt4-dev |
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| 8 | |
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| 9 | Package: tspsg |
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| 10 | Architecture: any |
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| 11 | Depends: ${shlibs:Depends}, ${misc:Depends} |
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| 12 | Description: TSP Solver and Generator |
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| 13 | TSPSG is intended to generate and solve Travelling Salesman Problem |
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| 14 | (TSP) tasks. It uses Branch and Bound method for solving. Its input is |
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| 15 | a number of cities and a matrix of city-to-city travel costs. The |
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| 16 | matrix can be populated with random values in a given range (which is |
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| 17 | useful for generating tasks). The result is an optimal route, its |
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| 18 | price, step-by-step matrices of solving and a solving graph. The task |
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| 19 | can be saved in an internal binary format and opened later. The result |
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| 20 | can be printed or saved as PDF, HTML, or ODF. |
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| 21 | . |
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| 22 | TSPSG may be useful for teachers to generate test tasks or just for |
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| 23 | regular users to solve TSPs. Also, it may be used as an example of |
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| 24 | using Branch and Bound method to solve a particular task. |
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| 25 | XB-Maemo-Display-Name: TSPSG |
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| 26 | XB-Maemo-Icon-26: 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 |
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