首页 | 本学科首页   官方微博 | 高级检索  
     


Hardware-oriented ant colony optimization
Affiliation:1. SAP Research, Vincenz-Prießnitz-Str. 1, 76131 Karlsruhe, Germany;2. Department of Computer Science, University of Leipzig, Johannisgasse 26, 04103 Leipzig, Germany;1. School of Data Science and Computer, Sun Yat-sen University, Guangzhou 510275, PR China;2. Collaborative Innovation Center of High Performance Computing, Sun Yat-sen University, Guangzhou 510275, PR China;1. School of Energy and Power Engineering, Beihang University, Beijing 100191, China;2. Department of Mechanical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China;3. School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, China;1. CITER Center for Innovation and Technology Research, Department of Industrial Management, Tampere University of Technology, PO Box 541, FI-33101 Tampere, Finland;2. Department of Automation Science and Engineering, Tampere University of Technology, PO Box 692, FI-33101, Tampere, Finland;1. Department of Civil Engineering, Shahid Bahonar University of Kerman, Kerman, Iran;2. Department of Civil Engineering, University of Birjand, Birjand, Iran
Abstract:A new kind of ant colony optimization (ACO) algorithm is proposed that is suitable for an implementation in hardware. The new algorithm – called Counter-based ACO – allows to systolically pipe artificial ants through a grid of processing cells. Various features of this algorithm have been designed so that it can be mapped easily to field-programmable gate arrays (FPGAs). Examples are a new encoding of pheromone information and a new method to define the decision sequence of ants. Experimental results that are based on simulations for the traveling salesperson problem and the quadratic assignment problem are presented to evaluate the proposed techniques.
Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号