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Continuous Population-Based Incremental Learning with Mixture Probability Modeling for Dynamic Optimization Problems.

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The effects of asymmetric neighborhood assignment in the MOEA/D algorithm.. Appl. Soft Comput., (2014)Solving the parameterless firefighter problem using multiobjective evolutionary algorithms. Proceedings of the Genetic and Evolutionary Computation Conference Companion, page 1321--1328. (2019)ED-LS: a heuristic local search for the firefighter problem.. GECCO (Companion), page 25-26. ACM, (2018)Evolutionary algorithm with a directional local search for multiobjective optimization in combinatorial problems.. GECCO (Companion), page 7-8. ACM, (2017)Local Search Based on a Local Utopia Point for the Multiobjective Travelling Salesman Problem.. IDEAL, volume 9375 of Lecture Notes in Computer Science, page 281-289. Springer, (2015)Simheuristics for the Multiobjective Nondeterministic Firefighter Problem in a Time-Constrained Setting., and . EvoApplications (2), volume 9598 of Lecture Notes in Computer Science, page 248-265. Springer, (2016)Analysis of Dynamic Properties of Stock Market Trading Experts Optimized with an Evolutionary Algorithm.. EvoApplications, volume 8602 of Lecture Notes in Computer Science, page 264-275. Springer, (2014)Feature selection in corporate credit rating prediction., and . Knowl. Based Syst., (2013)Continuous Population-Based Incremental Learning with Mixture Probability Modeling for Dynamic Optimization Problems., , , , and . IDEAL, volume 8669 of Lecture Notes in Computer Science, page 457-464. Springer, (2014)Auto-adaptation of Genetic Operators for Multi-objective Optimization in the Firefighter Problem.. IDEAL, volume 8669 of Lecture Notes in Computer Science, page 484-491. Springer, (2014)