Differential Evolution (DE) is a simple and efficient optimizer, especially for continuous
optimization. For these reasons DE has often been employed for solving various …

Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter
optimization algorithms in current use. DE operates through similar computational steps as …

Nature-Inspired Optimization Algorithms, Second Edition provides an introduction to all
major nature-inspired algorithms for optimization. The book's unified approach, balancing …

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 …

Data clustering is a popular unsupervised data mining tool that is used for partitioning a
given dataset into homogeneous groups based on some similarity/dissimilarity metric …

Many design problems in engineering are typically multiobjective, under complex nonlinear
constraints. The algorithms needed to solve multiobjective problems can be significantly …

Engineering optimisation is typically multi-objective and multidisciplinary with complex
constraints, and the solution of such complex problems requires efficient optimisation …

This article provides a general overview of the field now known as" evolutionary multi-
objective optimization," which refers to the use of evolutionary algorithms to solve problems …

Multiobjective design optimization problems require multiobjective optimization techniques
to solve, and it is often very challenging to obtain high-quality Pareto fronts accurately. In this …

Abstract Design problems in industrial engineering often involve a large number of design
variables with multiple objectives, under complex nonlinear constraints. The algorithms for …