Title :
Improving the Performance of Heuristic Searches with Judicious Initial Point Selection
Author :
Tahaee, S.A. ; Jahangir, A.H. ; Habibi-Masouleh, H.
Author_Institution :
Comput. Eng. Dept., Sharif Univ. of Technol., Tehran
Abstract :
In this paper we claim that local optimization can produce proper start point for genetic search. We completely test this claim on partitioning problem and on the performance of genetic search in a real problem that is finding aggregation tree in the sensor networks. The presented method (named Tendency algorithm) increases the performance of heuristic searches, and can be used in parallel with other tuning methods. The paper justifies the logic behind tendency algorithm by measuring the "entropy" of solution (in regard to optimal solution), and by numerous empirical tests.
Keywords :
entropy; optimisation; tree searching; Tendency algorithm; aggregation tree; entropy; genetic search; heuristic searches; judicious initial point selection; local optimization; partitioning problem; sensor networks; Acoustic sensors; Costs; Embedded computing; Entropy; Genetic algorithms; Genetic engineering; Hamming distance; Intelligent sensors; Logic testing; Partitioning algorithms; Aggregation Tree; Genetic Search; Hardware/Software Partitioning; Sensor Networks; Simulated Annealing; Tabu Search;
Conference_Titel :
Embedded Computing, 2008. SEC '08. Fifth IEEE International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-0-7695-3348-3
DOI :
10.1109/SEC.2008.65