期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
Polarimetric synthetic aperture radar (PolSAR) image classification is a vital application in remote sensing image processing. In recent years, deep l......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
In offline data-driven evolutionary optimization, no real fitness evaluations is allowed during the optimization, making it extremely challenging to b......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
Multimodal Multi-objective Optimization Problems (MMOPs) refer to the problems that have multiple Pareto-optimal solution sets in decision space corre......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
This paper proposes a novel bicriteria assisted adaptive operator selection (B-AOS) strategy for decomposition-based multiobjective evolutionary algor......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
The distributed assembly permutation flow-shop scheduling problem (DAPFSP) is a typical NP-hard combinatorial optimization problem that has wide appli......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 63 ()
In the domain of evolutionary computation, more and more attention has been paid to dynamic multiobjective optimization. Generally, artificial benchma......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 63 ()
Traditional multiobjective immune algorithms (MOIAs) widely use the domination relationship and crowding distance metric to run the cloning operator, ......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
Selection in evolutionary algorithms (EAs) selects promising solutions from a set of candidates. Most selection strategies are fitness-driven, where e......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
Most of existing image segmentation algorithms are only based on the color feature. However, the spatial distribution of an image can not be well desc......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 62 ()
Locating multiple optima and maintaining these identified solutions are two crucial issues in solving multimodal optimization problems (MMOPs). To add......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
The current many-objective evolutionary algorithms (MaOEAs) generally adopt the mutation strategies designed for single-objective optimization problem......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 64 ()
This paper proposes a novel nature-inspired method, so-called ripple-spreading algorithm (RSA) for multi-objective path optimization problem (MOPOP). ......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
Rather than a whole Pareto optimal front(POF), which demands too many points, the decision maker (DM) may only be interested in a partial region, call......
期刊： SWARM AND EVOLUTIONARY COMPUTATION, 2021; 60 ()
Many practical productions are full of significant uncertainties. For example, the working environment may change, machines may breakdown, workers may......
