Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Multiple Objective Optimization with Vector Evaluated Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Evolving Dynamic Multi-Objective Optimization Problems with Objective Replacement
Artificial Intelligence Review
Comparison of Multiobjective Evolutionary Algorithms: Empirical Results
Evolutionary Computation
Multi-objective test problems, linkages, and evolutionary methodologies
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Dynamic multi-objective optimization with evolutionary algorithms: a forward-looking approach
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Adaptive genetic algorithms applied to dynamic multiobjective problems
Applied Soft Computing
Dynamic Multi-objective Optimization Evolutionary Algorithm
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
A New Dynamic Multi-objective Optimization Evolutionary Algorithm
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 05
Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Towards high speed multiobjective evolutionary optimizers
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Evolutionary Multiobjective Optimization for Dynamic Hospital Resource Management
EMO '09 Proceedings of the 5th International Conference on Evolutionary Multi-Criterion Optimization
Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms
Evolutionary Multi-objective Optimization in Uncertain Environments: Issues and Algorithms
Using Diversity as an Additional-objective in Dynamic Multi-objective Optimization Algorithms
ISECS '09 Proceedings of the 2009 Second International Symposium on Electronic Commerce and Security - Volume 01
A competitive-cooperative coevolutionary paradigm for dynamic multiobjective optimization
IEEE Transactions on Evolutionary Computation - Special issue on computational finance and economics
Multiobjective optimization problems with complicated Pareto sets, MOEA/D and NSGA-II
IEEE Transactions on Evolutionary Computation
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Memetic algorithm for dynamic bi-objective optimization problems
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization
EMO'07 Proceedings of the 4th international conference on Evolutionary multi-criterion optimization
The parallel single front genetic algorithm (PSFGA) in dynamic multi-objective optimization
IWANN'07 Proceedings of the 9th international work conference on Artificial neural networks
The construction of dynamic multi-objective optimization test functions
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
An investigation on noise-induced features in robust evolutionary multi-objective optimization
Expert Systems with Applications: An International Journal
Handling uncertainties in evolutionary multi-objective optimization
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
Proceedings of the 12th annual conference on Genetic and evolutionary computation
New Dynamic Multiobjective Evolutionary Algorithm with Core Estimation of Distribution
ICECE '10 Proceedings of the 2010 International Conference on Electrical and Control Engineering
Information Sciences: an International Journal
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
New evolutionary algorithm for dynamic multiobjective optimization problems
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Clonal selection algorithm for dynamic multiobjective optimization
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Dynamic multiobjective optimization problems: test cases, approximations, and applications
IEEE Transactions on Evolutionary Computation
Multiswarms, exclusion, and anti-convergence in dynamic environments
IEEE Transactions on Evolutionary Computation
A review of multiobjective test problems and a scalable test problem toolkit
IEEE Transactions on Evolutionary Computation
A data mining approach to evolutionary optimisation of noisy multi-objective problems
International Journal of Systems Science - Computational intelligence optimisation in the presence of uncertainties
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Algorithms that solve Dynamic Multi-Objective Optimisation Problems (DMOOPs) should be tested on benchmark functions to determine whether the algorithm can overcome specific difficulties that can occur in real-world problems. However, for Dynamic Multi-Objective Optimisation (DMOO), no standard benchmark functions are used. A number of DMOOPs have been proposed in recent years. However, no comprehensive overview of DMOOPs exist in the literature. Therefore, choosing which benchmark functions to use is not a trivial task. This article seeks to address this gap in the DMOO literature by providing a comprehensive overview of proposed DMOOPs, and proposing characteristics that an ideal DMOO benchmark function suite should exhibit. In addition, DMOOPs are proposed for each characteristic. Shortcomings of current DMOOPs that do not address certain characteristics of an ideal benchmark suite are highlighted. These identified shortcomings are addressed by proposing new DMOO benchmark functions with complicated Pareto-Optimal Sets (POSs), and approaches to develop DMOOPs with either an isolated or deceptive Pareto-Optimal Front (POF). In addition, DMOO application areas and real-world DMOOPs are discussed.