On the Use of Survival Selection Methods for Evolutionary Diversity Optimisation

2026-06-19

AI Summary

This work addresses the limitation of conventional survival selection in evolutionary diversity optimization, which often fails due to its dependence on pairwise solution diversity. To overcome this issue, we propose a novel framework that enables the synchronous generation of multiple candidate solutions per generation, along with a tailored survival selection mechanism designed specifically for this setting. By moving beyond the traditional paradigm of single-solution, sequential updates, our approach effectively handles the dynamic nature of each solution’s contribution to population diversity. Experimental results demonstrate that, under certain conditions, the proposed multi-solution generation strategy accelerates convergence toward diverse solutions and significantly improves both the spread and quality balance of the final solution set.

Abstract

Generating a diverse set of high quality solutions for an optimisation problem has been studied extensively in recent years by the evolutionary computation community. A paradigm that has received increasing attention is evolutionary diversity optimisation (EDO), where the goal is to maximise the diversity of a solution set subject to quality constraints. Since the contribution of each solution to the diversity of the population depends on other solutions and can change dramatically if several solutions in the population are modified simultaneously, most EDO approaches generate a single new solution per generation and discard the solution with the least contribution to diversity, ensuring a steady increase in population diversity over successive generations until convergence. In this study, we aim to answer two questions: (1) Is generating multiple solutions in each generation beneficial for EDO? (2) How can this be achieved efficiently, given that conventional survival selection methods do not work well in EDO due to the dependency of a solution's contribution to diversity on other solutions?

Problem

• evolutionary diversity optimisation
• survival selection
• population diversity
• quality constraints
• multi-solution generation

Innovation

• evolutionary diversity optimisation
• survival selection
• population diversity
• multi-solution generation
• quality-diversity trade-off