Asynchronous-climb monkey algorithm for optimal sensor placement
Received:May 15, 2012  Revised:June 25, 2012
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DOI:10.7511/jslx201305001
KeyWord:asynchronous-climb monkey algorithm  optimal sensor placement  dual-structure coding method  variable learning factor  Guangzhou new TV tower
        
AuthorInstitution
伊廷华 大连理工大学 建设工程学部 土木工程学院, 大连
张旭东 大连理工大学 建设工程学部 土木工程学院, 大连
李宏男 大连理工大学 建设工程学部 土木工程学院, 大连
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Abstract:
      A novel asynchronous-climb monkey algorithm for optimal sensor placement is presented to solve the problems of sightless search and low efficiency in the key climb process of the monkey algorithm.The dual-structure coding method is adopted to overcome the disadvantage that the original monkey algorithm can only perform the optimization on continuous variables.The search pattern is improved by the information of global optimal solution and previous best solution during the search process of monkey population.Meanwhile,the asynchronous variable learning factor is introduced into the search pattern to maintain the balance of global and local search by adjusting the effect of monkeys' own and social experiences during the climb process,which greatly improve the search efficiency of the algorithm.Finally,the parametric sensitivity analysis and selection of optimal sensor placement are performed on Guangzhou new TV tower.The results show that the asynchronous-climb monkey algorithm is efficient and effective for sensor placement problem compared to the monkey algorithm.