activity
20202022
most citedAn Easy-to-use Real-world Multi-objective Optimization Problem Suite

316 citations · 942 across the 15 of their papers we have counts for

collaborators

15 papers

cs.NE2022

Benchmarking the Hooke-Jeeves Method, MTS-LS1, and BSrr on the Large-scale BBOB Function Set

Ryoji Tanabe

This paper investigates the performance of three black-box optimizers exploiting separability on the 24 large-scale BBOB functions, including the Hooke-Jeeves method, MTS-LS1, and…

math.OC20223 cited

A Two-phase Framework with a Bézier Simplex-based Interpolation Method for Computationally Expensive Multi-objective Optimization

Ryoji Tanabe, Youhei Akimoto, Ken Kobayashi +3

This paper proposes a two-phase framework with a Bézier simplex-based interpolation method (TPB) for computationally expensive multi-objective optimization. The first phase in TPB…

cs.NE20215 cited

Towards Exploratory Landscape Analysis for Large-scale Optimization: A Dimensionality Reduction Framework

Ryoji Tanabe

Although exploratory landscape analysis (ELA) has shown its effectiveness in various applications, most previous studies focused only on low- and moderate-dimensional problems. Thu…

cs.NE20203 cited

TPAM: A Simulation-Based Model for Quantitatively Analyzing Parameter Adaptation Methods

Ryoji Tanabe, Alex Fukunaga

While a large number of adaptive Differential Evolution (DE) algorithms have been proposed, their Parameter Adaptation Methods (PAMs) are not well understood. We propose a Target f…

cs.NE202085 cited

Reviewing and Benchmarking Parameter Control Methods in Differential Evolution

Ryoji Tanabe, Alex Fukunaga

Many Differential Evolution (DE) algorithms with various parameter control methods (PCMs) have been proposed. However, previous studies usually considered PCMs to be an integral co…

cs.NE202011 cited

How Far Are We From an Optimal, Adaptive DE?

Ryoji Tanabe, Alex Fukunaga

We consider how an (almost) optimal parameter adaptation process for an adaptive DE might behave, and compare the behavior and performance of this approximately optimal process to…