DocumentCode :
2121091
Title :
Enhancement of SA algorithm by intelligent time schedule
Author :
Shojaee, K. ; Behnam, M. ; Shakouri, H. ; Rezaei, M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Tehran, Tehran, Iran
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
1768
Lastpage :
1774
Abstract :
In this paper we present a glancing review of how to define the time schedule of Simulated Annealing (SA) algorithm in different articles that applied them to solve the traveling salesman problem(TSP). In the following subjects we introduce a new definition of this concept in relation to other parameters. In other word, we claim a novel description of initial temperature,Markov chain and final temperature to the basic algorithm of SA that gives an introduction to New Time Schedule Simulated Annealing (NTSSA). In this method, the dynamic coincidence of time schedule parameters and temperature conditions is a possible happening among the searching process. In continuation we present the obtaining results of proposed algorithm in solving TSP in comparison with basic methods of SA and other intelligent optimization methods. The surprising improvement in results obtained by this approach shows the efficiency of NTSSA in contrast with other basic optimization methods.
Keywords :
Markov processes; scheduling; search problems; simulated annealing; travelling salesman problems; Markov chain; SA algorithm; intelligent optimization; intelligent time schedule; searching process; simulated annealing; temperature conditions; time schedule parameter; traveling salesman problem; Algorithm design and analysis; Convergence; Markov processes; Schedules; Temperature distribution; Temperature measurement; Combinatorial Optimization; Simulated Annealing; Time Schedule; Traveling Salesman Problems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5573961
Link To Document :
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