Two adaptive mutation operators for optima tracking in dynamic optimization problems with evolution strategies

The dynamic optimization problem concerns finding an optimum in a changing environment. In the tracking problem, the optimizer should be able to follow the optimum’s changes over time. In this paper we present two adaptive mutation operators designed to improve the following of a timechanging optimum, under the assumption that the changes follow a non-random law. Such law can be estimated in order to improve the optimum tracking capabilities of the algorithm. For experimental assessment, a (1,λ) evolution strategy has been applied to a dynamic version of the sphere problem. Categories and Subject Descriptors I.2 [Computing Methodologies]: Artificial Intelligence; I.2.8 [Problem Solving, Control Methods, and Search]: Heuristic methods General Terms Algorithms Keywords Evolution strategies, dynamic optimization, tracking problem, time-varying fitness function.

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Claudio Rossi, Antonio Barrientos, Jaime del Cerro
• Keywords: Dynamic Optimization Problem, GECCO 2007, Optimum Tracking Capabilities, Tracking Problem