Evaluating the Bio-Inspired Optimization Algorithms: Modern Performance Indicators and (Non-parametric) Statistical Testing Framework

Speaker:  Swagatam Das – Kolkata, India
Topic(s):  Applied Computing

Abstract

A multitude of bio-inspired optimization algorithms continuously emerge to address the immense complexities inherent in non-convex, multi-modal, and multi-dimensional optimization problems, which are pervasive across various scientific and engineering domains. This presentation aims to standardize the terminology used in expressing concepts related to bio-inspired computing. It will also shed light on the procedure for benchmarking such algorithms, particularly when applied to single-objective problems with bound constraints and continuous parameters. Additionally, the talk will explore the necessity for employing advanced non-parametric statistical tests within benchmarking experiments, outlining some of the most widely recognized test techniques. In conclusion, the presentation will address outstanding issues concerning the performance evaluation of nature-inspired heuristics and the potential mappings from problems to algorithms.

About this Lecture

Number of Slides:  120
Duration:  90 minutes
Languages Available:  English
Last Updated: 

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