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 …

Path-relinking is a major enhancement to the basic greedy randomized adaptive search
procedure (GRASP), leading to significant improvements in solution time and quality. Path …

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 …

GRASP is a multi-start metaheuristic for combinatorial optimization problems, in which each
iteration consists basically of two phases: construction and local search. The construction …

This chapter discusses the principles and foundations behind scatter search and its
application to the problem of training neural networks. Scatter search is an evolutionary …

Greedy randomized adaptive search procedures, or GRASP, were introduced by T. Feo and
M. Resende in 1989 as a probabilistic heuristic for solving hard set covering problems. Soon …

The emergence of metaheuristics for solving difficult combinatorial optimization problems is
one of the most notable achievements of the last two decades in operations research. This …

A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for
combinatorial optimization. It is a multi‐start or iterative process, in which each GRASP …

We present a state-of-the-art survey of parallel meta-heuristic developments and results,
discuss general design and implementation principles that apply to most meta-heuristic …

In the job shop scheduling problem (JSP), a finite set of jobs is processed on a finite set of
machines under certain constraints, such that the maximum completion time of the jobs is …