As the world moves towards industrialization, optimization problems become more
challenging to solve in a reasonable time. More than 500 new metaheuristic algorithms …

A bilevel programming model represents the relationship in a specific decision process that
involves decisions within a hierarchical structure of two levels. The upper-level problem is …

Metaheuristic algorithms are computational intelligence paradigms especially used for
sophisticated solving optimization problems. This chapter aims to review of all …

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

Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its
metaphor from flowers proliferation role in plants. This paper provides a comprehensive …

Hybrid algorithms play a prominent role in improving the search capability of algorithms.
Hybridization aims to combine the advantages of each algorithm to form a hybrid algorithm …

This article presents an overview of metaheuristics as high-level soft computing strategies
for solving optimisation problems. A general view of the field is presented, and a review of …

Portfolio optimization involves the optimal assignment of limited capital to different available
financial assets to achieve a reasonable trade-off between profit and risk objectives. In this …

Many systems or applications have been developed for distributed environments with the
goal of attaining multiple objectives in the face of environmental challenges such as high …

This paper performs an unprecedented comparative study of Metaheuristic optimization
frameworks. As criteria for comparison a set of 271 features grouped in 30 characteristics …