A Review of Population-Based Metaheuristics for Large-Scale Black-Box Global Optimization—Part II

This article is the second part of a two-part survey series on large-scale global optimization. The first covered two major algorithmic approaches to optimization, namely, decomposition methods and hybridization methods, such as memetic algorithms local search. In this part, we focus sampling variation operators, approximation surrogate modeling, initialization parallelization. We also cover range problem areas in relation multiobjective constraint handling, overlapping components, component imbalance issue benchmarks, applications. includes discussion pitfalls challenges current research identifies several potential future research.