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 classes, instantiate these principles for the three meta-heuristic classes currently most extensively used—genetic methods, simulated annealing, and tabu search, and identify a number of trends and promising research directions
International audienceLocal Search metaheuristics are a recognized means of solving hard combinatori...
We propose a new distributed and parallel meta-heuristic framework to address the issues of scalabil...
In recent years, there have been significant advances in the theory and application of meta-heuristi...
Metaheuristic parallel search methods -- tabu search, simulated annealing and genetic algorithms, es...
In single-objective optimization it is possible to find a global optimum, while in the multi-objecti...
This talk provides a complete background on metaheuristics and presents in a unified view the main d...
We address the issue of using parallel implementations as a mean for efficient experimenting and fin...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
The increasing exploration of alternative methods for solving optimization problems causes that para...
In this paper we present a classification of parallel tabu search metaheuristics based, on the one h...
In recent years, there have been significant advances in the theory and application of metaheuristic...
Metaheuristics are the most exciting development in approximate optimization techniques of the last ...
In this work, we will look at a class of very hard practical problems which can, currently, only be ...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
This paper presents a parallel evolutionary metaheuristic which includes different threads aimed at ...
International audienceLocal Search metaheuristics are a recognized means of solving hard combinatori...
We propose a new distributed and parallel meta-heuristic framework to address the issues of scalabil...
In recent years, there have been significant advances in the theory and application of meta-heuristi...
Metaheuristic parallel search methods -- tabu search, simulated annealing and genetic algorithms, es...
In single-objective optimization it is possible to find a global optimum, while in the multi-objecti...
This talk provides a complete background on metaheuristics and presents in a unified view the main d...
We address the issue of using parallel implementations as a mean for efficient experimenting and fin...
There are numerous optimisation problems for which heuristics are currently the only practical solut...
The increasing exploration of alternative methods for solving optimization problems causes that para...
In this paper we present a classification of parallel tabu search metaheuristics based, on the one h...
In recent years, there have been significant advances in the theory and application of metaheuristic...
Metaheuristics are the most exciting development in approximate optimization techniques of the last ...
In this work, we will look at a class of very hard practical problems which can, currently, only be ...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
This paper presents a parallel evolutionary metaheuristic which includes different threads aimed at ...
International audienceLocal Search metaheuristics are a recognized means of solving hard combinatori...
We propose a new distributed and parallel meta-heuristic framework to address the issues of scalabil...
In recent years, there have been significant advances in the theory and application of meta-heuristi...