Expensive optimization problem (EOP) widely exists in various significant real-world
applications. However, EOP requires expensive or even unaffordable costs for evaluating …

Evolutionary algorithms are widely used for solving multiobjective optimization problems but
are often criticized because of a large number of function evaluations needed …

With the increasing amount of distributed generation (DG) integrated into electrical
distribution networks, various operational problems, such as excessive power losses, over …

This chapter reviews applications of Memetic Algorithms in the areas of business analytics
and data science. This approach originates from the need to address optimization problems …

An integrated technique that embeds civilized swarm optimization (CSO) and Powell's
pattern search (PPS) method is proposed to search economic dispatch of combined heat …

In this study, a novel surrogate model assisted multiobjective memetic algorithm (SMOMA) is
developed for optimal pum** strategies of large-scale coastal groundwater problems. The …

Different surrogate-assisted strategies can greatly influence the optimization efficiency of
surrogate-assisted multi-objective evolutionary algorithms. By hybridizing two …

Surrogate-assisted evolutionary algorithms (SAEAs) are a promising approach for solving
expensive multiobjective optimization problems, but they often cannot address high …

A comprehensive understanding of nutrient transport patterns and clarification of pollutant
sources' load contributions are critical prerequisites for develo** scientific pollution control …

A large number of plug-in hybrid electric vehicles (PHEVs) have high mobility but a small
battery capacity; thus, these vehicles urgently need to make charging and discharging …