English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper proposes a two-phase framework with a B\'{e}zier simplex-basedinterpolation method (TPB) for computationally expensive multi-objectiveoptimization. The first phase in TPB aims to approximate a few Pareto optimalsolutions by optimizing a sequence of single-objective scalar problems. Thefirst phase in TPB can fully exploit a state-of-the-art single-objectivederivative-free optimizer. The second phase in TPB utilizes a B\'{e}ziersimplex model to interpolate the solutions obtained in the first phase. Thesecond phase in TPB fully exploits the fact that a B\'{e}zier simplex model canapproximate the Pareto optimal solution set by exploiting its simplex structurewhen a given problem is simplicial. We investigate the performance of TPB onthe 55 bi-objective BBOB problems. The results show that TPB performssignificantly better than HMO-CMA-ES and some state-of-the-art meta-model-basedoptimizers.

A Two-phase Framework with a B\'{e}zier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization