ant system algorithm has the advantages of positive feedback and efficient convergence in optimal searching, but it lacks initial pheromone, which greatly limits this algorithm's searching speed. Oriented to Platf...
详细信息
ISBN:
(纸本)0780387368
ant system algorithm has the advantages of positive feedback and efficient convergence in optimal searching, but it lacks initial pheromone, which greatly limits this algorithm's searching speed. Oriented to Platform-Based Design of system-on-a-Chip, we present a hardware/software bi-partitioning algorithm based on ant system algorithm with Initial Pheromone. The main ideas are: a). Reuse the partitioning result. of reference design provided by Platform-Based Design method as current design's initial partitioning, which is then converted into the initial pheromone needed by ant system algorithm. b). Search for the optimal partitioning scheme with the ant system algorithm based on the initial pheromone. Our algorithm adopts system level reusing feature of Platform-Based Design method to prevent the disadvantages of ant system algorithm. Experiments show our algorithm-improves the efficiency of ant system algorithm by an average of forty percent.
In this paper, antsystem (AS) optimization algorithm in continuous space[14,15] is under further study and used for other examples of optimum value searching of multi-minimum continuous function and another linear co...
详细信息
ISBN:
(纸本)0780372689
In this paper, antsystem (AS) optimization algorithm in continuous space[14,15] is under further study and used for other examples of optimum value searching of multi-minimum continuous function and another linear continuous function. The multi-minimum function of Rosenbrock function is chosen. The algorithm used is defined in detail in paper [14] and. [15]. In this paper, the general optimization error function for algorithm evaluation is modified, and the detail is given in another paper of the authors in WCICA'02 conference [16]. The applicability characters of AS application in continuous space optimization problems sire summarized at the end of this paper. The authors of this paper firmly believe that this paper will have reference meaning to intelligent theory and control application research area.
In this paper, antsystem (AS) optimization algorithm in continuous space[23,24] is used for examples of optimum value searching of continuous function. The algorithm used is defined in detail in paper [24]. In this p...
详细信息
ISBN:
(纸本)0780372689
In this paper, antsystem (AS) optimization algorithm in continuous space[23,24] is used for examples of optimum value searching of continuous function. The algorithm used is defined in detail in paper [24]. In this paper, the general evaluation parameters are defined. It considers the general optimization dynamics of the whole antsystem. Two evaluation functions are defined. Using the same example and same parameters setting in [24], this paper discussed the performance evaluation of the defined AS algorithm in continuous space.
The antsystem (AS) algorithm of Dorigo is a new computational paradigm, which is a stochastic combinatorial algorithm. It solves optimization problems by means of "ants", that is, agents with a very simple ...
详细信息
ISBN:
(纸本)0780370872
The antsystem (AS) algorithm of Dorigo is a new computational paradigm, which is a stochastic combinatorial algorithm. It solves optimization problems by means of "ants", that is, agents with a very simple basic capability, which mimic the behavior of real ants. The AS proposed by Dorigo has appealing features, but in its standard form it has some limitations. Applied to the Traveling Salesman Problem, the AS approach encounters difficulties when applied to random graphs. To remedy this, we design a new type of agent by using intensification and diversification strategies, based on the proposals of tabu search, in order to reach better solutions.
暂无评论