In combinatorial optimization, near-optimal algorithms such as metaheuristics allow to iteratively solve in a reasonable time NP-hard complex problems. Two main categories of metaheuristics are distinguished: population-based metaheuristics (P-metaheuristics) and solution-based metaheuristics (S-metaheuristics). P-metaheuristics are population-oriented as they manage a whole population of solut...

The majority of the algorithms used to solve hard optimization problems today are population metaheuristics. These methods are often presented under a purely algorithmic angle, while insisting on the metaphors which led to their design. We propose in this article to regard population metaheuristics as methods making evolution a probabilistic sampling of the objective function, either explicitly...

INTRODUCTION The Metaheuristics are general strategies for designing heuristic procedures with high performance. The term metaheuristic, which appeared in 1986 for the first time (Glover, 1986), is compound by the terms: " meta " , that means over or behind, and " heuristic ". Heuristic is the qualifying used for methods of solving optimization problems that are obtained from the intuition, exp...

In this paper, different metaheuristics applied on an air traffic control problem. This problem is a graph partitioning problem. It can be solved by classical methods which are spectral and multilevel methods. State-of-the-art public-domain graph partitioning packages, CHACO and METIS are used to resolve it. A comparison between results return by these packages and metaheuristics implementation...

Metaheuristics are generic search strategies that can be adapted to solve complex problems. This paper describes in simple terms the most popular metaheuristics for combinatorial optimization problems. It also emphasizes the main contributions of the Canadian research community in the development and application of metaheuristics.

In this paper, different metaheuristics applied on an air traffic control problem. This problem is a graph partitioning problem. It can be solved by classical methods which are spectral and multilevel methods. State-of-the-art public-domain graph partitioning packages, CHACO and METIS are used to resolve it. A comparison between results return by these packages and metaheuristics implementation...

We present improved algorithms based on the primal-dual paradigm, where the Handbook of Approximation Algorithms and Metaheuristics, Chapman. H.-J. Böckenhauer, J. Hromkovič, S. Seibert: Stability of approximation. In: T. F. Gonzalez (ed.): Handbook of Approximation Algorithms and Metaheuristics. Handbook of Approximation Algorithms and MetaHeuristics. Networks, in: Handbook of Algorithms for M...