Population-based incremental learning with memory scheme for changing environments
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Memory-based immigrants for genetic algorithms in dynamic environments
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A comparative study of immune system based genetic algorithms in dynamic environments
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Dominance learning in diploid genetic algorithms for dynamic optimization problems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Information Sciences: an International Journal
A self-organizing random immigrants genetic algorithm for dynamic optimization problems
Genetic Programming and Evolvable Machines
Multi-strategy ensemble particle swarm optimization for dynamic optimization
Information Sciences: an International Journal
UMDAs for dynamic optimization problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Investigating restricted tournament replacement in ECGA for non-stationary environments
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A self-organized criticality mutation operator for dynamic optimization problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Dual-population genetic algorithm for nonstationary optimization
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A diversity maintaining population-based incremental learning algorithm
Information Sciences: an International Journal
Evolvable Agents in Static and Dynamic Optimization Problems
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Genetic algorithms with memory-and elitism-based immigrants in dynamic environments
Evolutionary Computation
A Generalized Approach to Construct Benchmark Problems for Dynamic Optimization
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
A Critical Look at Dynamic Multi-dimensional Knapsack Problem Generation
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Improving prediction in evolutionary algorithms for dynamic environments
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Variable-Size Memory Evolutionary Algorithm to Deal with Dynamic Environments
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Genetic Algorithms with Elitism-Based Immigrants for Changing Optimization Problems
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Triggered Memory-Based Swarm Optimization in Dynamic Environments
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Hyper-learning for population-based incremental learning in dynamic environments
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Novel Associative Memory Retrieving Strategies for Evolutionary Algorithms in Dynamic Environments
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Adaptive primal-dual genetic algorithms in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Compound particle swarm optimization in dynamic environments
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Genetic algorithms with immigrants schemes for dynamic multicast problems in mobile ad hoc networks
Engineering Applications of Artificial Intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A particle swarm optimization based memetic algorithm for dynamic optimization problems
Natural Computing: an international journal
An analysis of the XOR dynamic problem generator based on the dynamical system
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
IEEE Transactions on Evolutionary Computation
Particle swarm optimization with composite particles in dynamic environments
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Perspectives in dynamic optimization evolutionary algorithm
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
A study on the mutation rates of a genetic algorithm interacting with a sandpile
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Information Sciences: an International Journal
Composite particle optimization with hyper-reflection scheme in dynamic environments
Applied Soft Computing
Evolutionary optimization in spatio-temporal fitness landscapes
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Associative memory scheme for genetic algorithms in dynamic environments
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
The sandpile mutation operator for genetic algorithms
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Analysing fitness landscape changes in evolutionary robots
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Expert Systems with Applications: An International Journal
A framework to hybridize PBIL and a hyper-heuristic for dynamic environments
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Evolutionary computation for dynamic optimization problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Evolutionary algorithms have been widely used for stationary optimization problems. However, the environments of real world problems are often dynamic. This seriously challenges traditional evolutionary algorithms. In this paper, the application of population-based incremental learning (PBIL) algorithms, a class of evolutionary algorithms, for dynamic problems is investigated. Inspired by the complementarity mechanism in nature a Dual PBIL is proposed, which operates on two probability vectors that are dual to each other with respect to the central point in the genotype space. A diversity maintaining technique of combining the central probability vector into PBIL is also proposed to improve PBIL’s adaptability in dynamic environments. In this paper, a new dynamic problem generator that can create required dynamics from any binary-encoded stationary problem is also formalized. Using this generator, a series of dynamic problems were systematically constructed from several benchmark stationary problems and an experimental study was carried out to compare the performance of several PBIL algorithms and two variants of standard genetic algorithm. Based on the experimental results, we carried out algorithm performance analysis regarding the weakness and strength of studied PBIL algorithms and identified several potential improvements to PBIL for dynamic optimization problems.