This paper proposes a multimodal multiobjective Differential Evolution optimization
algorithm (MMODE). The technique is conceived for deployment on problems with a Pareto …

Optimal Power Flow (OPF) is used for developing corrective strategies and to perform least
cost dispatches. In order to guide the decision making of power system operators a more …

Machine Learning for Materials Science provides the fundamentals and useful insight into
where Machine Learning (ML) will have the greatest impact for the materials science …

In recent years, fault detection and diagnosis for industrial processes have been rapidly
developed to minimize costs and maximize efficiency by taking advantages of cheap …

This paper proposes a new multiobjective estimation of distribution algorithm (EDA) based
on joint probabilistic modeling of objectives and variables. This EDA uses the …

Real-world applications such as image processing, signal processing, and others often
contain a sequence of computation intensive kernels, each represented in the form of a …

Determining the path for an evolutionary algorithm is crucial for its performance. Current
methods for sampling reference points guiding evolutionary algorithms are inadequate for …

Maintaining the diversity of the decision space is of great significance in multimodal
multiobjective optimization problems (MMOPs). Since the traditional Pareto-dominance …

Evolutionary Robotics allows robots with limited sensors and processing to tackle complex
tasks by means of sensory-motor coordination. In this article we show the first application of …

Due to its advantages, the outrigger braced system has been employed in high‐rise
structures for the last 3 decades. It is evident that the numbers and locations of outriggers in …