CISUC - Exploratory analysis of stochastic local search algorithms in biobjective optimization
CISUC

Exploratory analysis of stochastic local search algorithms in biobjective optimization

Authors



Book Chapter

Experimental Methods for the Analysis of Optimization Algorithms, pp. 209-222, Springer, November 2010

Cited by

Year 2015 : 10 citations

 On the Performance of Multiobjective Evolutionary Algorithms in Automatic Parameter Extraction of Power Diodes
D Prada, M Bellini, I Stevanovic
Power Electronics, 2015

 An Integer Linear Programming approach to the single and bi-objective Next Release Problem
N Veerapen, G Ochoa, M Harman, EK Burke
Information and Software, 2015

 Feedback-control operators for improved Pareto-set description: Application to a polymer extrusion process
EG Carrano, DG Coelho, A Gaspar-Cunha
Engineering Applications of Artificial Intelligence, 2015

 General subpopulation framework and taming the conflict inside populations
DV Vargas, J Murata, H Takano, ACB Delbem
Evolutionary computation, 2015

 Multi-Objective Tabu Search 2: First Technical Report
C Tsotskas, T Kipouros, MA Savill
University of Cranfield, 2015

 A Bug in the Multiobjective Optimizer IBEA: Salutary Lessons for Code Release and a Performance Re-Assessment
D Brockhoff
Evolutionary Multi-Criterion Optimization, 2015

 MOEA/D-HH: A Hyper-Heuristic for Multi-objective Problems
RA Gonçalves, JN Kuk, CP Almeida
Evolutionary Multi-Criterion Optimization, 2015

 Geometric Differential Evolution in MOEA/D: A Preliminary Study
S Zapotecas-Martínez, B Derbel, A Liefooghe
Advances in Artificial Intelligence and Soft Computing, 2015

 Multi-objective design of district metered areas in water distribution networks
Galdiero, Enzo
PhD thesis, Universita degli studi di Napoli, 2015

 Rafael Frederico Alexandre
Despacho Dinâmico de Frota de Caminhões Heterogênea em Minas a Céu Aberto via Algoritmos Evolucionários Multiobjetivo
PhD thesis, Universidade Federal de Minas Gerais, 2015

Year 2014 : 9 citations

 H.R. Maier, et al. Evolutionary algorithms and other metaheuristics in water resources: Current status, research challenges and future directions, Environmental Modelling & Software, Volume 62, December 2014, Pages 271–299

 I Tsoukalas, C Makropoulos, Multiobjective optimisation on a budget: Exploring surrogate modelling for robust multi-reservoir rules generation under hydrological uncertainty, Environmental Modelling & Software, 2014

 B Derbel, J Humeau, A Liefooghe, S Verel, Distributed Localized Bi-objective Search, European Journal of Operations Research, 2014

 MOEA/D with Tabu Search for multiobjective permutation flow shop scheduling problems, A Alhindi, Q Zhang, CEC 2014

 Carrano, et al. Feedback-control operators for improved Pareto-set description: Application to a polymer extrusion process, Engineering Applications of Artificial Intelligence, Volume 38, February 2015, Pages 147–167

 T Tušar, B Filipi?, Initial experiments in visualization of empirical attainment function differences using maximum intensity projection, GECCO 2014

 T Tušar, B Filipi?, Visualizing Exact and Approximated 3D Empirical Attainment Functions, Mathematical Problems in Engineering, 2014

 B Derbel, D Brockhoff, A Liefooghe, S Verel , On the Impact of Scalarizing Functions on Evolutionary Multiobjective Optimization, Research Report] RR-8512, INRIA, 2014

 K Van Moffaert, MM Drugan, A Nowé, Learning Sets of Pareto Optimal Policies, AAMAS 2014

Year 2013 : 7 citations

 JM Szemis, GC Dandy, HR Maier, A multiobjective ant colony optimization approach for scheduling environmental flow management alternatives with application to the River Murray, Australia, Water Resources Research, 2013

 Fehervari, Istvan, Trianni, Vito, Elmenreich, Wilfried, On the Effects of the Robot Configuration on Evolving Coordinated Motion Behaviors, 2013 IEEE Congress on Evolutionary Computation (CEC), 1209 - 1216, 2013

 T. Tušar and B. Filipic, "An approach to visualizing the 3D empirical attainment function," in GECCO '13 Companion Proceedings, Fifteenth Annual Conference on Genetic and Evolutionary Computation (C. Blum, ed.), pp. 1367-1372, 2013.

 Bilel Derbel, Dimo Brockhoff, Arnaud Liefooghe, Force-Based Cooperative Search Directions in Evolutionary Multi-objective Optimization, Evolutionary Multi-Criterion Optimization, Lecture Notes in Computer Science Volume 7811, pp 383-397, 2013

 Iryna Yevseyeva, Vitor Basto Fernandes, David Ruano-Ordás, José R. Méndez: , Optimising anti-spam filters with evolutionary algorithms, Expert Syst. Appl. 40(10): 4010-4021, 2013

 Pedro Amorim, Carlos Henggeler Antunes, Bernardo Almada-Lobo, A Dual Mutation Operator to Solve the Multi-objective Production Planning of Perishable Goods, Advances in Metaheuristics Operations Research/Computer Science Interfaces Series Volume 53, pp 77-97, 2013

 Ignacio G. del Amo, David A. Pelta, SRCS: A Technique for Comparing Multiple Algorithms under Several Factors in Dynamic Optimization Problems, Metaheuristics for Dynamic Optimization, Studies in Computational Intelligence Volume 433, 2013, pp 61-77

Year 2011 : 2 citations

 Jaqueline S. Angelo, Helio J.C. Barbosa, On Ant Colony Algorithms for Multiobjective Optimization, Avi Ostfeld (ed), Ant Colony Optimization - Methods and Applications, InTech, 2011

 P Cheng, J.-S. Pan, L. Li, Y. Tang, C. Huang, A Survey of Performance Assessment for Multiobjective Optimizers, Fifth International Conference on Genetic and Evolutionary Computing (ICGEC), IEEE Computer Society, pp. 341 - 345, 2011

Year 2009 : 2 citations

 Jérémie Dubois-Lacoste, A study of Pareto and Two-Phase Local Search Algorithms for Biobjective Permutation Flowshop Scheduling, MSc thesis, Université Libre de Bruxelles, 2009.

 Jérémie Dubois-Lacoste. Weight Setting Strategies for Two-Phase Local Search: A Study on Biobjective Permutation Flowshop Scheduling. SLS-DS 2009: Doctoral Symposium on Engineering Stochastic Local Search Algorithms. Technical Report TR/IRIDIA/2009-024, IRIDIA, Université Libre de Bruxelles, Belgium, September 2009.