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蚁群算法应用于化学化工的现状与展望 被引量:1

The expectation and status quo on applications of ant colony algorithm in chemistry and chemical engineering
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摘要 蚁群法是继遗传法、模拟退火法和禁忌搜索法之外的又一种新兴,启发式随机搜索算法,该算法是模拟蚂蚁在觅食过程中,能发现蚁巢到食物的最短路径搜索机制而发展起来的,已成功地应用于一系列复杂组合问题的优化。本文主要综述蚁群法的基本原理,以及近5年来在化学化工中的应用情况。首先概述算法的特点,再详尽讨论建立蚁群法模型的有关抽象与近似,指出蚁群法的实现过程;从化学化工过程的优化、化学计量学的研究和催化剂的开发、化学反应动力学参数估算等方面,讨论了算法在化学化工领域中应用情况;最后展望算法在化学化工领域中的应用可能。 The ant colony algorithm, another novel meta-heuristic, evolutive, and stochastic search algorithm besides genetic algorithm, tabu search algorithm, and simulated annealing algorithm, which was developed from simulating the techniques employed by real ants to rapidly establish the shortest route from food source to their nest and vice versa, has been successfully used to achieve better solution to complicated combinatorial optimization problems. This review focused on the basic theory of the algorithm and it' s applications in chemistry and chemical engineering over the preceding 5-year period. First, an overview of the general features of the algorithm was given, followed by the discussion of several approximation and abstract techniques useful for modeling the related algorithm in detail. This article continued to discuss the actualizing technic from both the mathematic formulations and implementation procedure. Recent studies on the applications of the ant colony algorithm in chemistry and chemical engineering from optimization of chemical process, study of chemometric, development of catalyzer, and estimation of kinetic parameter points of view were then reviewed. Finally, expectation of future research on potential application in chemistry and chemical engineering of ant colony algorithm was presented.
出处 《计算机与应用化学》 CAS CSCD 北大核心 2007年第8期1138-1144,共7页 Computers and Applied Chemistry
关键词 蚁群算法 化学 化工 应用现状 展望 ant colony algorithm, modeling, chemistry, chemical engineering, applications, expectation
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  • 1吴庆生,丁亚平.高灵敏四阶导数光谱PLS法同时测定钨钼钛[J].光谱学与光谱分析,1995,15(4):119-124. 被引量:10
  • 2马良.多准则货郎问题及其算法.运筹学的理论与应用[M].西安:西安电子科技大学出版社,1996.187-192.
  • 3蔡利剑.智能蚂蚁系统研究[M].天津:河北工业大学,2001..
  • 4David R,Ignas G N.Ad Hoc networking in future wireless communications [J].Computer Communications,2003,26(1):36-40.
  • 5Chenxi Z,Corson M S.QoS routing for mobile Ad Hoc networks [A].Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies,New York,2002.
  • 6Kwang M S,Weng H S.Ant colony optimization for routing and load-balancing:survey and new directions [J].IEEE Transactions on Systems,Man and Cybernetics:Part A,2003,33(5):560-572.
  • 7Hussein O,Saadawi T.Ant routing algorithm for mobile ad-hoc networks (ARAMA) [A].2003 IEEE International Performance,Computing,and Communications Conference,Phoenix,USA,2003.
  • 8Shen C C,Jaikaeo C.Ad Hoc multicast routing algorithm with swarm intelligence [J].ACM Mobile Networks and Applications Journal,2005,10(1-2):47-59.
  • 9Dorigo M,DiCaro G,Gambardella L M.Ant algorithms for discrete optimization [J].Artificial Life,1999,5(2):137-172.
  • 10Dadebo S A, Mcauley K B. Dynamic optimization of constrained chemical engineering problems using dynamic programming [J].Computers and Chemical Engineering, 1995, 19(5): 513-525.

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