Now showing items 1-3 of 3
Less detectable environmental changes in dynamic multiobjective optimisation
(ACM Press, 2018-05-04)
Multiobjective optimisation in dynamic environments is challenging due to the presence of dynamics in the problems in question. Whilst much progress has been made in benchmarks and algorithm design for dynamic multiobjective ...
An empirical study of dynamic triobjective optimisation problems
(IEEE Press, 2018-07)
Dynamic multiobjective optimisation deals with multiobjective problems whose objective functions, search spaces, or constraints are time-varying during the optimisation process. Due to wide presence in real-world applications, ...
Accelerating differential evolution based on a subset-to-subset survivor selection operator
Differential evolution (DE) is one of the most powerful and effective evolutionary algorithms for solving global optimization problems. However, just like all other metaheuristics, DE also has some drawbacks, such as slow ...