Now showing items 51-60 of 121
Benchmark Generator for the IEEE WCCI-2014 Competition on Evolutionary Computation for Dynamic Optimization Problems: Dynamic Travelling Salesman Problem Benchmark Generator
(De Montfort University, U.K., 2013-10)
In this report, the dynamic benchmark generator for permutation-encoded problems for the travelling salesman problem (DBGPTSP) proposed in is used to convert any static travelling salesman problem benchmark to a dynamic ...
Multi-line distance minimization: A visualized many-objective test problem suite
Studying the search behavior of evolutionary manyobjective optimization is an important, but challenging issue. Existing studies rely mainly on the use of performance indicators which, however, not only encounter increasing ...
A green intelligent routing algorithm supporting flexible QoS for many-to-many multicast
The tremendous energy consumption attributed to the Information and Communication Technology (ICT) field has become a persistent concern during the last few years, attracting significant academic and industrial efforts. ...
Improving the Multiobjective Evolutionary Algorithm Based on Decomposition with New Penalty Schemes
It has been increasingly reported that the multiobjective optimization evolutionary algorithm based on decomposition (MOEA/D) is promising for handling multiobjective optimization problems (MOPs). MOEA/D employs scalarizing ...
Training neural networks with ant colony optimization algorithms for pattern classification
Feed-forward neural networks are commonly used for pattern classification. The classification accuracy of feed-forward neural networks depends on the configuration selected and the training process. Once the architecture ...
Evolutionary computation for dynamic optimization problems
(ACM Press, 2013-07)
An Improved Multiobjective Optimization Evolutionary Algorithm Based on Decomposition for Complex Pareto Fronts
The multi-objective evolutionary algorithm based on decomposition (MOEA/D) has shown to be very efficient in solving multi-objective optimization problems (MOPs). In practice, the Pareto-optimal front (POF) of many MOPs ...
A framework of scalable dynamic test problems for dynamic multi-objective optimization
(IEEE Press, 2014-12)
Dynamic multi-objective optimization has received increasing attention in recent years. One of striking issues in this field is the lack of standard test suites to determine whether an algorithm is capable of solving dynamic ...
An adaptive multi-swarm optimizer for dynamic optimization problems
(The MIT Press, 2014-01-17)
The multi-population method has been widely used to solve dynamic optimization problems (DOPs) with the aim of maintaining multiple populations on different peaks to locate and track multiple changing optima simultaneously. ...
Guest editorial: Computational intelligence for cloud computing
(IEEE Press, 2018-02)