A modified PSO with fuzzy inference system for solving the planar graph coloring problem
There are several optimization problems with number of feasible solution is polynomial bounded by the size of the given input instances. Graph Coloring is a classic NP-hard problem; hence, it is theoretically of great importance. Diverse applications of Graph Coloring have made the scientific commun...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/16547/7/MostafaErfaniMFSKSM2010.pdf |
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| Summary: | There are several optimization problems with number of feasible solution is polynomial bounded by the size of the given input instances. Graph Coloring is a classic NP-hard problem; hence, it is theoretically of great importance. Diverse applications of Graph Coloring have made the scientific community to be constantly searching for elegant solutions. Some of these applications are communication network, mobile radio frequency, computer register allocation, printed circuit board testing, time tabling and scheduling, pattern matching and Sudoku games. Many solutions have been proposed by the previous studies on solving Graph Coloring problems. But the most recent and efficient approach is commonly based on hybrid algorithms that use a particular kind of recombination operator. Hence, this study proposes a modified particle swarm optimization with fuzzy logic to obtain a high performance algorithm for solving the Planar Graph Coloring problem. Experimental results on several randomly generated graphs have illustrated the efficiency of the proposed method accordingly. |
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