Geodesy

Algorithm

Benchmark (surveying)

Control (management)

Ecology

Biology

Computer science

Mathematical optimization

Classical mechanics

Type (biology)

Physics

Mathematics

Optics

Geography

Fuzzy logic

Meta heuristic

Artificial intelligence

Interval (graph theory)

Heuristic

Combinatorics

Acceleration

Control theory (sociology)

Adaptation (eye)

Heuristics

Information Sciences

In this paper a method for dynamically adjusting parameters in meta-heuristics based on interval type-2 fuzzy logic is proposed. Nowadays meta-heuristic algorithms have become a powerful choice in solving complex optimization problems. The gravitational search algorithm (GSA) based on the Newton laws of gravity and acceleration can be used to solve optimization problems achieving good results, however like in other optimization algorithms a critical issue is an appropriate adjustment of its parameters depending on the type of problem. In this paper the main contribution is a proposed method aimed at dynamic parameter adjustment in GSA with the help of type-2 fuzzy logic. Simulation results on benchmark problems show the advantages of the proposed approach.

Interval type-2 fuzzy logic for dynamic parameter adaptation in a modified gravitational search algorithm