Previous researchers have made impressive strides in developing algorithms and solution
methodologies to address multi-objective optimization (MOO) problems in industrial …

Multimodal multiobjective optimization aims to find all Pareto optimal solutions, including
overlapping solutions in the objective space. Multimodal multiobjective optimization has …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

Multimodal multiobjective problems (MMOPs) arise frequently in the real world, in which
multiple Pareto-optimal solution (PS) sets correspond to the same point on the Pareto front …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

The immune system is a remarkable information processing and self learning system that
offers inspiration to build artificial immune system (AIS). The field of AIS has obtained a …

The artificial immune network (AIN), a computational intelligence model based on artificial
immune systems inspired by the vertebrate immune system, has been widely utilized for …

In the past decades, various effective and efficient multi-objective evolutionary algorithms
(MOEAs) have been proposed for solving multi-objective optimization problems. However …

Abstract Multi-objective (MO) optimization, ie, the simultaneous optimization of multiple
conflicting objectives, is gaining more and more attention in various research areas, such as …

This review paper attempts to position the area of Artificial Immune Systems (AIS) in a
broader context of interdisciplinary research. We review AIS based on an established …