Now showing items 1-6 of 6
The effect of diversity maintenance on prediction in dynamic multi-objective optimization
There are many dynamic multi-objective optimization problems (DMOPs) in real-life engineering applications whose objectives change over time. After an environmental change occurs, prediction strategies are commonly used ...
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 ...
A Pareto-based evolutionary algorithm using decomposition and truncation for dynamic multi-objective optimization
Maintaining a balance between convergence and diversity of the population in the objective space has been widely recognized as the main challenge when solving problems with two or more conflicting objectives. This is added ...
Novel prediction strategies for dynamic multi-objective optimization
(IEEE Press, 2019-06-13)
This paper proposes a new prediction-based dynamic multi-objective optimization (PBDMO) method, which combines a new prediction-based reaction mechanism and a popular regularity model-based multi-objective estimation of ...
Solving dynamic multi-objective problems with an evolutionary multi-directional search approach
The challenge of solving dynamic multi-objective optimization problems is to effectively and efficiently trace the varying Pareto optimal front and/or Pareto optimal set. To this end, this paper proposes a multi-direction ...
An evolutionary dynamic multi-objective optimization algorithm based on center-point prediction and sub-population autonomous guidance
Dynamic multi-objective optimization problems (DMOPs) provide a challenge in that objectives conflict each other and change over time. In this paper, a hybrid approach based on prediction and autonomous guidance is proposed, ...