Multimodal optimization amounts to finding multiple global and local optima (as opposed to
a single solution) of a function, so that the user can have a better knowledge about different …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

This paper provides a survey of the research done on optimization in dynamic environments
over the past decade. We show an analysis of the most commonly used problems, methods …

Clearly, nature has been very effective in creating organisms that are capable of protecting
themselves against a wide variety of pathogens such as bacteria, fungi, and parasites. The …

We explore the usage of the modal possibility operator (and its dual necessity operator) in
qualitative data analysis, and show that it-quite literally-complements the derivation operator …

Multi-objective immune algorithm (MOIA) is a heuristic algorithm based on artificial immune
system model. Due to its characteristics of antibody clonal selection, automatic antigen …

Dynamic environments abound and offer particular challenges for all optimisation and
problem solving methods. A well-known strategy for survival in dynamic environments is to …

Artificial Immune Systems (AIS) are computational paradigms that belong to the
computational intelligence family and are inspired by the biological immune system. During …

This paper presents a new methodology to solve the reconfiguration problem of electrical
distribution systems (EDSs) with variable demand, using the artificial immune algorithm Copt …

A novel metaheuristic for continuous optimization problems, named the virus optimization
algorithm (VOA), is introduced and investigated. VOA is an iteratively population-based …