Using data mining technique for coefficient tuning of an adaptive Tabu search
Date Issued
2007-09-09
Author(s)
Gjorgjevikj, Dejan
Loshkovska, Suzana
Abstract
This paper describes the Adaptive Tabu Search
algorithm (A-TS), an improved tabu search algorithm for
combinatorial optimization. A-TS uses a novel approach for
evaluation of the moves, incorporated in a new complex
evaluation function. A new decision making mechanism
triggers the evaluation function providing means for
avoiding possible infinite loops. The new evaluation function
implements effective diversification strategy that prevents
the search from stagnation. It also incorporates two
adaptive coefficients that control the influence of the
aspiration criteria and the long-term memory, respectively.
The adaptive nature of A-TS is based on these two adaptive
coefficients. This article also presents a new data mining
approach towards improving the performance of A-TS by
tuning these coefficients. A-TS performance is applied to the
Quadratic Assignment Problem. Published results from
other authors are used for comparison. The experimental
results show that A-TS performs favorably against other
established techniques.
algorithm (A-TS), an improved tabu search algorithm for
combinatorial optimization. A-TS uses a novel approach for
evaluation of the moves, incorporated in a new complex
evaluation function. A new decision making mechanism
triggers the evaluation function providing means for
avoiding possible infinite loops. The new evaluation function
implements effective diversification strategy that prevents
the search from stagnation. It also incorporates two
adaptive coefficients that control the influence of the
aspiration criteria and the long-term memory, respectively.
The adaptive nature of A-TS is based on these two adaptive
coefficients. This article also presents a new data mining
approach towards improving the performance of A-TS by
tuning these coefficients. A-TS performance is applied to the
Quadratic Assignment Problem. Published results from
other authors are used for comparison. The experimental
results show that A-TS performs favorably against other
established techniques.
Subjects
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