Now showing items 31-40 of 207
A many-objective evolutionary algorithm based on rotated grid
Evolutionary optimization algorithms, a meta-heuristic approach, often encounter considerable challenges in many-objective optimization problems (MaOPs). The Pareto-based dominance loses its effectiveness in MaOPs, which ...
Evolutionary Computation for Dynamic Optimization Problems
(ACM Press, 2015-07)
Many real-world optimization problems are subject to dynamic environments, where changes may occur over time regarding optimization objectives, decision variables, and/or constraint conditions. Such dynamic optimization ...
Artificially inducing environmental changes in evolutionary dynamic optimization
Biological and artificial evolution can be speeded up by environmental changes. From the evolutionary computation perspective, environmental changes during the optimization process generate dynamic optimization problems ...
Evolutionary Dynamic Multiobjective Optimization: Benchmarks and Algorithm Comparisons
Dynamic multi-objective optimization has received growing research interest in recent years since many real-world optimization problems appear to not only have multiple objectives that conflict with each other but also ...
A particle swarm optimization based memetic algorithm for dynamic optimization problems.
Recently, there has been an increasing concern from the evolutionary computation community on dynamic optimization problems since many real-world optimization problems are dynamic. This paper investigates a particle swarm ...
A hybrid evolutionary multiobjective approach for the dynamic component selection problem.
Component selection is a crucial problem in Component Based Software Engineering (CBSE). CBSE is concerned with the assembly of pre-existing software components that leads to a software system that responds to client-specific ...
Dynamic vehicle routing: A memetic ant colony optimization approach
A hybrid genetic algorithm and tabu search approach for post enrolment course timetabling.
(Springer Science & Business, 2011)
The post enrolment course timetabling problem (PECTP) is one type of university course timetabling problems, in which a set of events has to be scheduled in time slots and located in suitable rooms according to the student ...
ETEA: A Euclidean minimum spanning tree-based evolutionary algorithm for multiobjective optimization
(MIT Press, 2014-05)
The Euclidean minimum spanning tree (EMST), widely used in a variety of domains, is a minimum spanning tree of a set of points in space where the edge weight between each pair of points is their Euclidean distance. Since ...
Ant colony optimization with immigrants schemes for the dynamic vehicle routing problem.
Ant colony optimization (ACO) algorithms have proved to be able to adapt to dynamic optimization problems (DOPs) when they are enhanced to maintain diversity and transfer knowledge. Several approaches have been integrated ...