• Archana Gupta
• Sanjaya Kumar Sahu

Global optimization finds wide applications in almost all branches of engineering, physical sciences, applied sciences, social science, finance, and management. It is the task of finding the absolutely best set of admissible conditions to achieve objective, the global minimum. Extensive efforts have been made to address the issue and many global optimization methods have been developed. The global optimization methods are classified into groups deterministic and stochastic depending on whether or not they incorporate any stochastic elements. The two broad classes of global optimization deterministic and stochastic have their own benefiting features and limitations. In recent years many modified algorithms of both the classes have been developed. Hybridization of algorithms of different classes is the newly arisen concept in the field of global optimization. This paper surveys the research work done in the field of global optimization.

global optimization; deterministic methods; stochastic methods; hybrid algorithms

"Global Optimization Methods: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.102-109, March-2019, Available :http://www.jetir.org/papers/JETIR1903I18.pdf

"Global Optimization Methods: A Review", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp102-109, March-2019, Available at : http://www.jetir.org/papers/JETIR1903I18.pdf