Scalability of optimization algorithms is a major challenge in co** with the ever-growing
size of optimization problems in a wide range of application areas from high-dimensional …

Memetic computing is a subject in computer science which considers complex structures
such as the combination of simple agents and memes, whose evolutionary interactions lead …

Research in metaheuristics for combinatorial optimization problems has lately experienced
a noteworthy shift towards the hybridization of metaheuristics with other techniques for …

This study provides guidelines for the selection of proper goodness-of-fit criteria for the
calibration and evaluation of hydrological models. Popular goodness-of-fit criteria and good …

Memetic Algorithms (MAs) are computational intelligence structures combining multiple and
various operators in order to address optimization problems. The combination and …

Large-scale optimization problems (LSOPs) are challenging because the algorithm is
difficult in balancing too many dimensions and in esca** from trapped bottleneck …

Group formation is a complex task requiring computational support to succeed. In the
literature, there has been considerable effort in the development of algorithms for composing …

In this paper, a global optimum-based search strategy is proposed to alleviate the situation
that the differential evolution (DE) usually sticks into a stagnation, especially on complex …

Structural bias is a recently identified property of optimisation algorithms, causing them to
favour certain regions of the search space over others, independently of the objective …

Nowadays, a promising way to obtain hybrid metaheuristics concerns the combination of
several search algorithms with strong specialization in intensification and/or diversification …