Now showing items 161-170 of 170
A guided search non-dominated sorting genetic algorithm for the multi-objective university course timetabling problem.
The university course timetabling problem is a typical combinatorial optimization problem. This paper tackles the multi-objective university course timetabling problem (MOUCTP) and proposes a guided search non-dominated ...
Benchmark generator for the IEEE WCCI-2012 competition on evolutionary computation for dynamic optimization problems. Technical Report 2011.
(Department of Information Systems and Computing, Brunel University., 2011)
Shuffle Or Update Parallel Differential Evolution for Large-Scale Optimization
This paper proposes a novel algorithm for large-scale optimization problems. The proposed algorithm, namely shuffle or update parallel differential evolution (SOUPDE) is a structured population algorithm characterized by ...
A brief analysis of evolutionary algorithms for the dynamic multiobjective subset sum problem.
(Babes-Bolyai University, Faculty of Mathematics and Computer Science., 2011)
The paper investigate the behavior of evolutionary algorithms for solving multiobjective combinatorial problems in dynamic environments. Present work envisages the multiobjective subset sum problem which is known as an ...
Disturbed exploitation compact differential evolution for limited memory optimization problems
This paper proposes a novel and unconventional Memetic Computing approach for solving continuous optimization problems characterized by memory limitations. The proposed algorithm, unlike employing an explorative evolutionary ...
A memetic ant colony optimization algorithm for the dynamic travelling salesman problem.
Ant colony optimization (ACO) has been successfully applied for combinatorial optimization problems, e.g., the travelling salesman problem (TSP), under stationary environments. In this paper, we consider the dynamic TSP ...
Subgroup Discovery: Real-World Applications
(Techincal Report, 2011-03-01)
Subgroup discovery is a data mining technique which extracts interesting rules with respect to a target variable. An important characteristic of this task is the combination of predictive and descriptive induction. In ...
Subgroup Discovery trhough Evolutionary Fuzzy Systems applied to Bioinformatic problems
(Technical Report DMU, 2011-03-01)
Subgroup discovery is a descriptive data mining technique using supervised learning. This paper presents a summary about the main properties and elements about subgroup discovery task. In addition, we will focus on the ...