The simulation-driven metaheuristic algorithms have been successful in solving numerous
problems compared to their deterministic counterparts. Despite this advantage, the …

We review the literature on executing production schedules in the presence of unforeseen
disruptions on the shop floor. We discuss a number of issues related to problem formulation …

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 …

Internet of things (IoT) facilitates billions of devices to be enabled with network connectivity
to collect and exchange real-time information for providing intelligent services. Thus, IoT …

This book provides a handbook of algorithmic recipes from the fields of Metaheuristics,
Biologically Inspired Computation and Computational Intelligence that have been described …

Selection methods have an important role in the meta-heuristic search (MHS) process.
However, apart from a few successful methods developed in the past, new and effective …

Comparing, or benchmarking, of optimization algorithms is a complicated task that involves
many subtle considerations to yield a fair and unbiased evaluation. In this paper, we …

Abstract Stochastic Fractal Search (SFS) is a new and original meta-heuristic search (MHS)
algorithm with strong foundations. As with many other MHS methods, there are problems in …

Metaheuristics are a relatively new but already established approach to combinatorial
optimization. A metaheuristic is a generic algorithmic template that can be used for finding …

The field of parallel metaheuristics is continuously evolving as a result of new technologies
and needs that researchers have been encountering. In the last decade, new models of …