| Author: | Wong, Chi-fai Ivan |
| Title: | A hybrid order-based genetic algorithm solution to the classified advertisements layout problem |
| Degree: | M.Sc. |
| Year: | 1999 |
| Subject: | Advertising layout and typography -- Data processing Genetic algorithms Advertising, Classified -- Data processing Advertising, Newspaper -- Data processing Hong Kong Polytechnic University -- Dissertations |
| Department: | Multi-disciplinary Studies Department of Computing |
| Pages: | viii, 106 leaves : ill. ; 31 cm |
| Language: | English |
| Abstract: | The aim of this dissertation is to describe the hybrid order-based genetic algorithms for solving the classified advertisements layout problem in newspaper. The classified advertisements layout problem is simply to find a layout for the classified advertisements, so that the newspaper pages are fully utilization and the appearance of the newspaper pages is tidy and professional. An existing solution of this problem based on greedy algorithms will be described. After reviewing the related literature, it is found that the problem is a special case of the general "bin-packing" problems. Since the "bin-packing" problems are "NP-complete", the classified advertisements layout problem is also "NP-complete". Therefore, an exact and efficient algorithm for solving the classified advertisements layout problem there should not be exists. Although "bin-packing" problems are "NP-complete", some classical algorithms have been developed and proved to have guaranteed performances. The description of these classical algorithms will also be provided. It was found that one of the classical algorithms, the "First Fit Decreasing" (FFD) is very similar to the existing solution based on greedy algorithm. In order to improve the result provided by the existing algorithms, the existing algorithm is hybridized to genetic algorithms to form a hybrid order-based genetic algorithm for this particular problem. Then the performance of this hybrid order-based genetic algorithm is tested by comparing the performance of this algorithm with the classified algorithms and with the algorithms based on random variables. Since the genetic algorithm and the algorithms for comparison have the probabilistic nature, the comparison is actually a statistic on the performance after a number of independent try runs. |
| Rights: | All rights reserved |
| Access: | restricted access |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| b14605314.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 3.38 MB | Adobe PDF | View/Open |
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