Multimodal optimization (MMO) aiming to locate multiple optimal (or near-optimal) solutions
in a single simulation run has practical relevance to problem solving across many fields …

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

Metaheuristics for Hard Optimization comprises of three parts. The first part is devoted to the
detailed presentation of the four most widely known metaheuristics:• the simulated …

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

Heuristic optimization provides a robust and efficient approach for solving complex real-
world problems. The focus of this research is on a hybrid method combining two heuristic …

A Rosenbrock artificial bee colony algorithm (RABC) that combines Rosenbrock's rotational
direction method with an artificial bee colony algorithm (ABC) is proposed for accurate …

This paper considers the development of a novel hybrid metaheuristic algorithm which is
proposed to achieve an optimum design for automobile cruise control (ACC) system by …

This paper proposes PSACO (particle swarm ant colony optimization) algorithm for highly
non-convex optimization problems. Both particle swarm optimization (PSO) and ant colony …

Two novel extensions for the well known ant colony optimization (ACO) framework are
introduced here, which allow the solution of mixed integer nonlinear programs (MINLPs) …

Flexible manufacturing system (FMS) enhances the firm's flexibility and responsiveness to
the ever-changing customer demand by providing a fast product diversification capability …