Genetic Algorithms Demo: Multimodal Function Optimization - III (Deb, Saha)

As opposed to a unimodal function optimization, where we find only "the" best solution, the task in a multimodal optimization problem is to find ALL the good solutions. See how it happens.

This demo is based on my work: Deb, K., Saha, A., "Finding Multiple Solutions for Multimodal Optimization Problems Using a Multi-Objective Evolutionary Approach "(Accepted to be presented as full paper in GECCO-2010).

This is a 2-variable variant of the unconstrained MMP(n) function proposed in the paper. It has 48-optima- one global and 47 local optima. The video shows the variables x1 and x2 "settling" in their optima.

Category:

Education

Tags:

• genetic algorithms
• AI
• Demo