Multi-objective genetic algorithms: Problem difficulties and construction of test problems
Evolutionary Computation
Dynamic multiobjective optimization problems: test cases, approximation, and applications
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Multi-swarm co-evolutionary paradigm for dynamic multi-objective optimisation problems
International Journal of Intelligent Information and Database Systems
Benchmarks for dynamic multi-objective optimisation algorithms
ACM Computing Surveys (CSUR)
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Dynamic Multi-objective Optimization Problems (DMOPs) gradually become a difficult and hot topic in Multi-objective Optimization area. However, there is lack of standard test functions for Dynamic Multi-objective Optimization Algorithms now. Firstly this paper proves the existence of Pareto optimal set of a class of a special non-dynamic two-objective optimization problem theoretically. Based on this result, we present one method of constructing dynamic two-objective and scalable multi-objective optimization problems, and then providing the test suites which are easy to be constructed and have known Pareto Optimal set and Pareto optimal front.