Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

As the population aging trend accelerates in many countries throughout the world, notably in
China, elderly-care services become increasingly vital. Institutional elderly-care services, a …

This paper combines the tabu search process with a genetic algorithm by employing a new
partial opposed-based as the population initialization technique to minimize makespan …

The genetic algorithm (GA) is a well-known metaheuristic approach for dealing with complex
problems with a wide search space. In genetic algorithms (GAs), the quality of individuals in …

Many new metaheuristic algorithms prioritize their search strategy phase, often neglecting
equally critical stages like initialization. Latin hypercube sampling (LHS) is one technique …

The two-volume set LNAI 7894 and LNCS 7895 constitutes the refereed proceedings of the
12th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2013 …

Legged robots have become a hot topic in robotics owing to their superior mobility. In this
study, a two-segment hydraulic robotic leg with the kinematic model is first presented. In this …

Integrating deep learning methods into metaheuristic algorithms has gained attention for
addressing design-related issues and enhancing performance. The primary objective is to …

A realistic and accurate product cost estimation is of high importance during the design
phases of products and assembly lines. This paper presents a methodology that aims at …

The purpose of instance selection is to reduce the data size while preserving as much useful
information stored in the data as possible and detecting and removing the erroneous and …