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dc.contributor.authorLong, Q.
dc.contributor.authorWu, Changzhi
dc.contributor.authorWang, Xiangyu
dc.contributor.authorWu, Z.
dc.identifier.citationLong, Q. and Wu, C. and Wang, X. and Wu, Z. 2017. A modified quasisecant method for global optimization. Applied Mathematical Modelling. 51: pp. 21-37.

© 2017 Elsevier Inc. This paper presents an algorithm for global optimization problem whose objective functions is Lipschitz continuous but not necessarily differentiable. The proposed algorithm consists of local and global search procedures which are based on and inspired by quasisecant method, respectively. The aim of the global search procedure is to identify “promising” basins in the search space. Once a promising basin is identified, the search procedure skips from an exhausted area to the obtained basin, and the local search procedure is then applied at this basin. It proves that the proposed algorithm converges to the global minimum solution if the local ones are finite and isolated. The proposed method is tested by academic benchmarks, numerical performance and comparison show that it is efficient and robust. Finally, The method is applied to solve the sensor localization problem.

dc.titleA modified quasisecant method for global optimization
dc.typeJournal Article
dcterms.source.titleApplied Mathematical Modelling
curtin.departmentDepartment of Construction Management
curtin.accessStatusFulltext not available

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