Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Advanced fitness landscape analysis and the performance of memetic algorithms
Evolutionary Computation - Special issue on magnetic algorithms
Generalized benchmark generation for dynamic combinatorial problems
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
Multi-objective test problems, linkages, and evolutionary methodologies
Proceedings of the 8th annual conference on Genetic and evolutionary computation
The Impact of Global Structure on Search
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
A polynomial time computation of the exact correlation structure of k-satisfiability landscapes
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
PISA: a platform and programming language independent interface for search algorithms
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
NK landscapes, problem difficulty, and hybrid evolutionary algorithms
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Advanced neighborhoods and problem difficulty measures
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Set-based multiobjective fitness landscapes: a preliminary study
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Exploratory landscape analysis
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A classification of dynamic multi-objective optimization problems
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Fitness-probability cloud and a measure of problem hardness for evolutionary algorithms
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Global characterization of the CEC 2005 fitness landscapes using fitness-distance analysis
EvoApplications'11 Proceedings of the 2011 international conference on Applications of evolutionary computation - Volume Part I
Performance of evolutionary algorithms on random decomposable problems
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Benchmarking evolutionary and hybrid algorithms using randomized self-similar landscapes
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
Dynamic combinatorial optimisation problems: an analysis of the subset sum problem
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary Optimization and Learning
Test-case generator for nonlinear continuous parameter optimizationtechniques
IEEE Transactions on Evolutionary Computation
A review of multiobjective test problems and a scalable test problem toolkit
IEEE Transactions on Evolutionary Computation
A behavior-based analysis of modal problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Recent advances in problem understanding: changes in the landscape a year on
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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Optimisation research often concentrates on developing heuristic methods for solving a given optimisation problem, however a growing body of work surrounds the understanding and analysis of the problem itself to facilitate heuristic development and selection. We outline the broad themes that this field encompasses, presenting some of the techniques and approaches that have been taken, and present a sociometric view of selected publications in the field. We conclude by proposing a collaborative system to allow researchers working on problem understanding to more easily share results and work together.