189 citations · 702 across the 38 of their papers we have counts for
25 papers · 1 filter
A Flexible and Generic Approach for Explainable Landscape Analysis and the pyXla Toolbox
Tony Ombaso, Anna S. Bosman, Arnaud Liefooghe +2
Landscape analysis has been successfully applied to understand complex optimisation problems, gain insights into algorithm behaviour, and automate algorithm selection and configura…
Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics ---22 Years of Paradiseo---
Johann Dreo, Arnaud Liefooghe, Sébastien Verel +5
The success of metaheuristic optimization methods has led to the development of a large variety of algorithm paradigms. However, no algorithm clearly dominates all its competitors…
An Analysis on Selection for High-Resolution Approximations in Many-Objective Optimization
Hernan Aguirre, Arnaud Liefooghe, Sébastien Verel +1
This work studies the behavior of three elitist multi- and many-objective evolutionary algorithms generating a high-resolution approximation of the Pareto optimal set. Several sear…
Local Optima Networks: A New Model of Combinatorial Fitness Landscapes
Gabriela Ochoa, Sébastien Verel, Fabio Daolio +1
This chapter overviews a recently introduced network-based model of combinatorial landscapes: Local Optima Networks (LON). The model compresses the information given by the whole s…
Clustering of Local Optima in Combinatorial Fitness Landscapes
Gabriela Ochoa, Sébastien Verel, Fabio Daolio +1
Using the recently proposed model of combinatorial landscapes: local optima networks, we study the distribution of local optima in two classes of instances of the quadratic assignm…
Analyzing the Effect of Objective Correlation on the Efficient Set of MNK-Landscapes
Sébastien Verel, Arnaud Liefooghe, Laetitia Jourdan +1
In multiobjective combinatorial optimization, there exists two main classes of metaheuristics, based either on multiple aggregations, or on a dominance relation. As in the single o…
On the Neutrality of Flowshop Scheduling Fitness Landscapes
Marie-Eleonore Marmion, Clarisse Dhaenens, Laetitia Jourdan +2
Solving efficiently complex problems using metaheuristics, and in particular local searches, requires incorporating knowledge about the problem to solve. In this paper, the permuta…
On the Effect of Connectedness for Biobjective Multiple and Long Path Problems
Sébastien Verel, Arnaud Liefooghe, Jérémie Humeau +2
Recently, the property of connectedness has been claimed to give a strong motivation on the design of local search techniques for multiobjective combinatorial optimization (MOCO).…
The Road to VEGAS: Guiding the Search over Neutral Networks
Marie-Eleonore Marmion, Clarisse Dhaenens, Laetitia Jourdan +2
VEGAS (Varying Evolvability-Guided Adaptive Search) is a new methodology proposed to deal with the neutrality property of some optimization problems. ts main feature is to consider…
First-improvement vs. Best-improvement Local Optima Networks of NK Landscapes
Gabriela Ochoa, Sébastien Verel, Marco Tomassini
This paper extends a recently proposed model for combinatorial landscapes: Local Optima Networks (LON), to incorporate a first-improvement (greedy-ascent) hill-climbing algorithm,…
Pareto Local Optima of Multiobjective NK-Landscapes with Correlated Objectives
Sébastien Verel, Arnaud Liefooghe, Laetitia Jourdan +1
In this paper, we conduct a fitness landscape analysis for multiobjective combinatorial optimization, based on the local optima of multiobjective NK-landscapes with objective corre…
Set-based Multiobjective Fitness Landscapes: A Preliminary Study
Sébastien Verel, Arnaud Liefooghe, Clarisse Dhaenens
Fitness landscape analysis aims to understand the geometry of a given optimization problem in order to design more efficient search algorithms. However, there is a very little know…
NILS: a Neutrality-based Iterated Local Search and its application to Flowshop Scheduling
Marie-Eleonore Marmion, Clarisse Dhaenens, Laetitia Jourdan +2
This paper presents a new methodology that exploits specific characteristics from the fitness landscape. In particular, we are interested in the property of neutrality, that deals…
DAMS: Distributed Adaptive Metaheuristic Selection
Bilel Derbel, Sébastien Verel
We present a distributed generic algorithm called DAMS dedicated to adaptive optimization in distributed environments. Given a set of metaheuristic, the goal of DAMS is to coordina…
Communities of Minima in Local Optima Networks of Combinatorial Spaces
Fabio Daolio, Marco Tomassini, Sébastien Verel +1
In this work we present a new methodology to study the structure of the configuration spaces of hard combinatorial problems. It consists in building the network that has as nodes t…
Do not Choose Representation just Change: An Experimental Study in States based EA
Maroun Bercachi, Philippe Collard, Manuel Clergue +1
Our aim in this paper is to analyse the phenotypic effects (evolvability) of diverse coding conversion operators in an instance of the states based evolutionary algorithm (SEA). Si…
The Connectivity of NK Landscapes' Basins: A Network Analysis
Sébastien Verel, Gabriela Ochoa, Marco Tomassini
We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces. We use the well-known family of…
A Study of NK Landscapes' Basins and Local Optima Networks
Gabriela Ochoa, Marco Tomassini, Sébastien Verel +1
We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces (Doye, 2002). We use the well-kno…
From Cells to Islands: An unified Model of Cellular Parallel Genetic Algorithms
David Simoncini, Philippe Collard, Sébastien Verel +1
This paper presents the Anisotropic selection scheme for cellular Genetic Algorithms (cGA). This new scheme allows to enhance diversity and to control the selective pressure which…
Evolving Dynamic Change and Exchange of Genotype Encoding in Genetic Algorithms for Difficult Optimization Problems
Maroun Bercachi, Philippe Collard, Manuel Clergue +1
The application of genetic algorithms (GAs) to many optimization problems in organizations often results in good performance and high quality solutions. For successful and efficien…
Neutral Fitness Landscape in the Cellular Automata Majority Problem
Sébastien Verel, Philippe Collard, Marco Tomassini +1
We study in detail the fitness landscape of a difficult cellular automata computational task: the majority problem. Our results show why this problem landscape is so hard to search…
How to use the Scuba Diving metaphor to solve problem with neutrality ?
Philippe Collard, Sébastien Verel, Manuel Clergue
We proposed a new search heuristic using the scuba diving metaphor. This approach is based on the concept of evolvability and tends to exploit neutrality which exists in many real-…
Scuba Search : when selection meets innovation
Sébastien Verel, Philippe Collard, Manuel Clergue
We proposed a new search heuristic using the scuba diving metaphor. This approach is based on the concept of evolvability and tends to exploit neutrality in fitness landscape. Desp…
Where are Bottlenecks in NK Fitness Landscapes?
Sébastien Verel, Philippe Collard, Manuel Clergue
Usually the offspring-parent fitness correlation is used to visualize and analyze some caracteristics of fitness landscapes such as evolvability. In this paper, we introduce a more…