The field of metaheuristics for the application to combinatorial optimization problems is a
rapidly growing field of research. This is due to the importance of combinatorial optimization …

Due to the stubborn nature of the deterministic job-shop scheduling problem many solutions
proposed are of hybrid construction cutting across the traditional disciplines. The problem …

Metaheuristics are widely recognized as efficient approaches for many hard optimization
problems. This paper provides a survey of some of the main metaheuristics. It outlines the …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

Faced with the challenge of solving hard optimization problems that abound in the real
world, classical methods often encounter great difficulty. Vitally important applications in …

In this paper, we present an improved and discrete version of the Cuckoo Search (CS)
algorithm to solve the famous traveling salesman problem (TSP), an NP-hard combinatorial …

The key idea underlying iterated local search is to focus the search not on the full space of
all candidate solutions but on the solutions that are returned by some underlying algorithm …

Artificial Intelligence is one of the most rapidly evolving subjects within the computing/
engineering curriculum, with an emphasis on creating practical applications from hybrid …

Ant System, the first Ant Colony Optimization algorithm, showed to be a viable method for
attacking hard combinatorial optimization problems. Yet, its performance, when compared to …

The importance of high performance algorithms for tackling difficult optimization problems
cannot be understated, and in many cases the only available methods are metaheuristics …