Department of Applied Mathematics & Physics, Kyoto University
Technical Report 2003-007 (June 21, 2003)
Tabu Search Directed by Direct Search Methods for Nonlinear Global Optimization
by Abdel-Rahman Hedar and Masao Fukushima
In recent years, there has been a great deal of interest in
metaheuristics in the optimization community. Tabu Search (TS)
represents a popular class of metaheuristics. However, compared
with other metaheuristics like genetic algorithm and simulated
annealing, contributions of TS that deal with continuous problems
are still very limited.
In this paper, we introduce a continuous TS called Directed Tabu
Search (DTS) method. In the DTS method, direct-search-based
strategies are used to direct a tabu search. These strategies are
based on the well-known Nelder-Mead method and a new pattern
search procedure called adaptive pattern search. Moreover, we
introduce a new tabu list conception with anti-cycling rules
called Tabu Regions and Semi-Tabu Regions. In addition,
Diversification and Intensification search schemes are employed.
Numerical results show that the proposed method is promising and
produces high quality solutions.