Now showing items 11-20 of 22
A Pareto-based many-objective evolutionary algorithm using space partitioning selection and angle-based truncation
Evolutionary algorithms (EAs) have shown to be efficient in dealing with many-objective optimization problems (MaOPs) due to their ability to obtain a set of compromising solutions which not only converge toward the Pareto ...
A loosely coupled hybrid meta-heuristic algorithm for the static independent task scheduling problem in grid computing
(IEEE Press, 2018-03)
Task scheduling is one of the most difficult problems in grid computing systems. Therefore, various studies have been proposed to present methods which provide efficient schedules. Meta-heuristic approaches are among the ...
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, ...
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 ...
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 ...
Hybrid meta-heuristic algorithms for independent job scheduling in grid computing
The term ’grid computing’ is used to describe an infrastructure that connects geographically distributed computers and heterogeneous platforms owned by multiple organizations allowing their computational power, storage ...
A multi-objective evolutionary algorithm based on coordinate transformation
(IEEE Press, 2018-05-28)
In this paper, a novel multiobjective evolutionary algorithm (MOEA/CT) is proposed to better manage convergence and distribution of solutions when MOEAs are used for solving multiobjective optimization problems. The ...
Ant colony optimization for dynamic combinatorial optimization problems
(The Institution of Engineering and Technology, 2018-02)
The ant colony optimization (ACO) metaheuristic was inspired from the foraging behaviour of real ant colonies. In particular, real ants communicate indirectly via pheromone trails and find the shortest path. Although real ...
Guest editorial: Computational intelligence for cloud computing
(IEEE Press, 2018-02)
An adaptive framework to tune the coordinate systems in evolutionary algorithms
(IEEE Press, 2018-03-12)
The performance of many nature-inspired optimization algorithms depends strongly on their implemented coordinate system. However, the commonly used coordinate system is fixed and not well suited for different function ...