A modified quasisecant method for global optimization
MetadataShow full item record
© 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.
Showing items related by title, author, creator and subject.
Chong, Yen N. (2001)General routing problems deal with transporting some commodities and/or travelling along the axes of a given network in some optimal manner. In the modern world such problems arise in several contexts such as distribution ...
Teunissen, Peter (2010)Global navigation satellite system (GNSS) carrier phase integer ambiguity resolution is the key to high-precision positioning and attitude determination. In this contribution, we develop new integer least-squares (ILS) ...
Woon, Siew Fang (2009)Optimal control problems arise in many applications, such as in economics, finance, process engineering, and robotics. Some optimal control problems involve a control which takes values from a discrete set. These problems ...