Multi-nuclear parallel ant group design method based on TBB

Abstract

The invention discloses a multinuclear parallel ant colony design method based on TBB, in particular a parallel ant colony algorithm designed by utilizing the superiority of TBB support and parallel computation of a multinuclear processor or by adopting a parallel object-oriented optimum method, through compiling relevant template classes, circulatory iteration and circulatory valuation during the most consumption in the ant colony algorithm are optimized, a solution process of each ant is distributed to different threads, and the multinuclear resource superiority of a computer is fully utilized. The design method realizes parallelization of the algorithm based on a serial ant colony algorithm which is basically unchanged, maintains an original design structure and refreshes pheromones byadopting the method combining serial computation with parallel computation. The invention has the advantages that the parallel optimum computational process is simple, flexible and easy to operate, and conforms to the tendency that the computer technology is developed toward multiple processors and multinuclear framework, and the operating time and the operating efficiency of the algorithm are improved, so as to provide the possibility of a real-time resolution of a large-scale combination and optimization project.

Description

technical field [0001] The invention relates to a multi-core parallel ant colony design method based on TBB (Thread Building Blocking), and belongs to the field of computer simulation and algorithm optimization. Background technique [0002] Combinatorial optimization of discrete systems is a problem often encountered in actual production, such as task allocation, job scheduling, path planning, network routing, data mining, life science computing and other problems. The rapid increase of , is called the NP-complexity puzzle. [0003] Since Dorigo M proposed the ant colony algorithm, the algorithm has achieved good results in solving this type of problems, but if the scale of the problem continues to expand, the time consumed by the single CPU-based serial ant colony algorithm will increase rapidly, and often Can not meet people's real-time computing needs. How to obtain a simple and applicable method to improve the running time efficiency of ant colony algorithm will be of...

AI Technical Summary

Problems solved by technology

[0004] An effective way to improve the operating efficiency of the ant colony algorithm is parallel design. Most of the existing parallel ant colony algorithms are implemented based on MPI (Message Passing Interface), but MPI design of parallel algorithms is relatively cumbersome, especially when dealing with data sharing and data During the exchange process, it is usually only suitable for parallel ant colony algorithms designed by professional programmers on computer clusters

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