%X This paper describes the origin and significant contribution on the development of the Hybrid Simulated Annealing and Genetic Algorithms (HSAGA) approach for finding global optimization. HSAGA provide an insight approach to handle in solving complex optimization problems. The method is, the combination of meta-heuristic approaches of Simulated Annealing and novel Genetic Algorithms for solving a non-linear objective function with uncertain technical coefficients in an industrial production management problems. The proposed novel hybrid method is designed to search for global optimal for the non-linear objective function and search for the best feasible solutions of the decision variables. Simulated experiments were carried out rigorously to reflect the advantages of the proposed method. A description of the well developed method and the advanced computational experiment with MATLAB technical tool is presented. An industrial production management optimization problem is solved using HSAGA technique. The results are very much promising. © 2009 American Institute of Physics.
%L scholars543
%J AIP Conference Proceedings
%O cited By 11; Conference of 2nd Global Conference on Power Control and Optimization, PCO'2009 ; Conference Date: 1 June 2009 Through 3 June 2009
%R 10.1063/1.3223938
%D 2009
%V 1159
%A P. Vasant
%A N. Barsoum
%T Hybrid Simulated Annealing and Genetic Algorithms for industrial production management problems
%C Bali
%P 254-261