Title :
Heuristics for graph decomposition
Author :
Tabbara, Hiba ; Dana, Tarek ; Mansour, Nashat
Author_Institution :
Comput. Sci. Program, Lebanese American Univ., Beirut, Lebanon
Abstract :
The problem addressed in this paper is that of decomposing a weighted graph into a specified number of subgraphs such that these subgraphs have balanced sums of vertex weights and minimal sums of edge weights. To find a reasonable solution to this intractable problem, we suggest an approximate objective function that can be minimized by heuristic procedures. The heuristic procedure that we propose is based on a hybrid genetic algorithm (HGA) for decomposing a graph followed by an iterative improvement heuristic for tuning the HGA´s results. We applied our proposed heuristics to several graphs and obtained promising results
Keywords :
genetic algorithms; graph theory; iterative methods; approximate objective function; balanced sums; edge weights; graph decomposition; heuristic procedures; hybrid genetic algorithm; iterative improvement heuristic; subgraphs; vertex weights; weighted graph; Biological cells; Computational modeling; Computer science; Electronic mail; Genetic algorithms;
Conference_Titel :
Electronics, Circuits and Systems, 2000. ICECS 2000. The 7th IEEE International Conference on
Conference_Location :
Jounieh
Print_ISBN :
0-7803-6542-9
DOI :
10.1109/ICECS.2000.912961
