Title
Heuristic pattern search and its hybridization with simulated annealing for nonlinear global optimization
Abstract
In this article, we present a new approach of hybrid simulated annealing method for minimizing multimodel functions called the simulated annealing heuristic pattern search (SAHPS) method. Two subsidiary methods are proposed to achieve the final form of the global search method, SAHPS. First, we introduce the approximate descent direction (ADD) method, which is a derivative-free procedure with high ability of producing a descent direction. Then, the ADD method is combined with a pattern search method with direction pruning to construct the heuristic pattern search (HPS) method. The last method is hybridized with simulated annealing (SA) to obtain the SAHPS method. The experimental results through well-known test functions are shown to demonstrate the efficiency of the proposed method SAHPS.
Year
DOI
Venue
2004
10.1080/10556780310001645189
OPTIMIZATION METHODS & SOFTWARE
Keywords
Field
DocType
unconstrained global optimization,descent direction,pattern search,metaheuristics,simulated annealing
Simulated annealing,Heuristic,Mathematical optimization,Nonlinear system,Global optimization,Descent direction,Mathematics,Pattern search,Metaheuristic
Journal
Volume
Issue
ISSN
19
3-4
1055-6788
Citations 
PageRank 
References 
31
1.63
9
Authors
2
Name
Order
Citations
PageRank
Abdel-Rahman Hedar140430.79
Masao Fukushima22050172.73