B. Dorronsoro

Publications173
h-index27
Citations3,067
Highly Influential Citations185
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MOCell: A cellular genetic algorithm for multiobjective optimization
TLDR
This paper introduces a new cellular genetic algorithm for solving multiobjective continuous optimization problems. Expand
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  • 39
  • PDF
AbYSS: Adapting Scatter Search to Multiobjective Optimization
TLDR
We propose the use of a hybrid metaheuristic algorithm called Archive-Based hYbrid Scatter Search (AbYSS), which follows the scatter search structure but uses mutation and crossover operators from evolutionary algorithms. Expand
  • 265
  • 20
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The exploration/exploitation tradeoff in dynamic cellular genetic algorithms
  • E. Alba, B. Dorronsoro
  • Mathematics, Computer Science
  • IEEE Transactions on Evolutionary Computation
  • 1 April 2005
TLDR
This paper studies static and dynamic decentralized versions of the cellular genetic algorithm, in which individuals are located in a specific topology and interact only with their neighbors. Expand
  • 314
  • 18
  • PDF
Improving Classical and Decentralized Differential Evolution With New Mutation Operator and Population Topologies
  • B. Dorronsoro, P. Bouvry
  • Mathematics, Computer Science
  • IEEE Transactions on Evolutionary Computation
  • 1 February 2011
TLDR
Differential evolution (DE) algorithms compose an efficient type of evolutionary algorithm (EA) for the global optimization domain. Expand
  • 126
  • 12
jMetal: a Java Framework for Developing Multi-Objective Optimization Metaheuristics
TLDR
This paper introduces jMetal, an object-oriented Java-based framework aimed at facilitating the development of metaheuristics for solving multi-objective optimization problems (MOPs). Expand
  • 168
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Solving the Vehicle Routing Problem by Using Cellular Genetic Algorithms
TLDR
In this paper we propose the utilization of some cGAs with and without including local search techniques for solving the vehicle routing problem (VRP). Expand
  • 107
  • 8
  • PDF
Computing nine new best-so-far solutions for Capacitated VRP with a cellular Genetic Algorithm
TLDR
This paper is devoted to solve the Capacitated VRP (CVRP), an extension of VRP, which is mainly characterized by using vehicles of the same capacity. Expand
  • 86
  • 7
  • PDF
Design Issues in a Multiobjective Cellular Genetic Algorithm
TLDR
We study a number of issues related to the design of a cellular genetic algorithm (cGA) for multiobjective optimization. Expand
  • 82
  • 6
Efficient Batch Job Scheduling in Grids using Cellular Memetic Algorithms
TLDR
In this work we exploit the capabilities of cellular memetic algorithms (cMAs) for obtaining efficient batch schedulers for grid systems. Expand
  • 76
  • 5
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A Study of the Combination of Variation Operators in the NSGA-II Algorithm
TLDR
This paper analyses whether a more dynamic approach combining different operators with variable application rate along the search process allows to improve the static classical behavior of multi-objective evolutionary algorithms. Expand
  • 19
  • 5