Paired Comparisons-based Interactive Differential Evolution

TL;DR

This paper introduces an interactive differential evolution method that reduces user fatigue by using paired comparisons instead of full individual comparisons, demonstrating faster convergence than existing methods.

Contribution

The paper presents a novel IDE approach based on paired comparisons, improving user experience and convergence speed over traditional IGA and tournament IGA.

Findings

Paired comparison approach reduces user fatigue.

Proposed IDE converges faster than IGA and tournament IGA.

User interface improvements enhance IEC performance.

Abstract

We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals each other but compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed one is superior to others from both user interface and convergence performance points of view.