The term “metaheuristics” was first proposed by Glover on 1986. The word “metaheuristics” contains all heuristics methods that show evidence of achieving good quality solutions for the problem of interest within an acceptable time. Usually, metaheuristics offer no guarantee of obtaining the global solutions.

Metaheuristics can be classified into two classes; population-based methods and point-to-point methods. In the latter methods, the search invokes only one solution at the end of each iteration from which the search will start in the next iteration. On the other hand, the population-based methods invoke a set of many solutions at the end of each iteration. Below, we highlight the principles of genetic algorithm as an example of population-based methods, and simulated annealing and tabu search as examples of point-to-point methods.

· Genetic Algorithm.

· Simulated Annealing.

· Tabu Search.