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An Extensible JCLEC-based Solution for the Implementation of Multi-Objective Evolutionary Algorithms

Published: 11 July 2015 Publication History

Abstract

The ongoing advances in multi-objective optimisation (MOO) are improving the way that complex real-world optimisation problems, mostly characterised by the definition of many conflicting objectives, are currently addressed. To put it into practice, developers require flexible implementations of these algorithms so that they can be adapted to the problem-specific needs. Here, metaheuristic optimisation frameworks (MOFs) are essential tools to provide end-user oriented development solutions. Even though consolidated MOFs are continuously evolving, they seem to have paid little attention to the new trends in MOO. Recently, new frameworks have emerged with the aim of providing support to these approaches, but they often offer less variety of basic functionalities like diversity of encodings and operators than other general-purpose solutions. In this paper we identify a number of relevant features serving to satisfy the requirements demanded by MOO nowadays, and propose a solution, called JCLEC-MOEA, on the basis of the JCLEC framework. As a key contribution, its architecture has been designed with a twofold purpose: reusing all the features already given by a mature framework like JCLEC, and extending it to enable new developments more flexibly than current alternatives.

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  1. An Extensible JCLEC-based Solution for the Implementation of Multi-Objective Evolutionary Algorithms

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      cover image ACM Conferences
      GECCO Companion '15: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation
      July 2015
      1568 pages
      ISBN:9781450334884
      DOI:10.1145/2739482
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      Publication History

      Published: 11 July 2015

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      Author Tags

      1. jclec
      2. many-objective evolutionary algorithms
      3. metaheuristic optimisation framework
      4. multi-objective evolutionary algorithms

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      • Spanish Ministry of Economy and Competitiveness
      • Spanish Ministry of Education

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      Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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      View all
      • (2024)Hypervolume-Based Cooperative Coevolution With Two Reference Points for Multiobjective OptimizationIEEE Transactions on Evolutionary Computation10.1109/TEVC.2023.328739928:4(1054-1068)Online publication date: Aug-2024
      • (2022)JGEAProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3520304.3533960(2009-2018)Online publication date: 9-Jul-2022
      • (2022)A hyper-parameter tuning approach for cost-sensitive support vector machine classifiersSoft Computing10.1007/s00500-022-06768-827:18(12863-12881)Online publication date: 2-Feb-2022
      • (2019)A Systematic Review of Interaction in Search-Based Software EngineeringIEEE Transactions on Software Engineering10.1109/TSE.2018.280305545:8(760-781)Online publication date: 1-Aug-2019
      • (2019)JCLEC-MOEngineering Applications of Artificial Intelligence10.1016/j.engappai.2019.02.00381:C(14-28)Online publication date: 1-May-2019
      • (2018)Interactive multi-objective evolutionary optimization of software architecturesInformation Sciences10.1016/j.ins.2018.06.034463-464(92-109)Online publication date: Oct-2018
      • (2017)On the effect of local search in the multi-objective evolutionary discovery of software architectures2017 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2017.7969551(2038-2045)Online publication date: Jun-2017

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