Cloud computing is a recently looming-evoked paradigm, the aim of which is to provide on-
demand, pay-as-you-go, internet-based access to shared computing resources (hardware …

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 …

Technological advances in the last two decades have aroused great interest in the class of
dynamic vehicle routing problems (DVRPs), which is reflected in the significant growth of the …

Warehouses deliver labor-intensive services to customers. Underperformance may result in
high costs and unsatisfied customer demand. New market developments force warehouses …

Fast growth of produced data from deferent smart devices such as smart mobiles, IoT/IIoT
networks, and vehicular networks running different specific applications such as Augmented …

Specialized data preparation techniques, ranging from data cleaning, outlier detection,
missing value imputation, feature selection (FS), amongst others, are procedures required to …

In recent years, the field of combinatorial optimization has witnessed a true tsunami of
“novel” metaheuristic methods, most of them based on a metaphor of some natural or man …

Feature selection is a process to reduce the dimension of a dataset by removing redundant
features, and to use the optimal subset of features for machine learning or data mining …

Activity-based scheduling optimization is a combinatorial problem built on the traveling
salesman problem intending to optimize people schedules considering their trips and the …