@article {10.3844/jcssp.2010.413.416, article_type = {journal}, title = {Convalesce Optimization for Input Allocation Problem Using Hybrid Genetic Algorithm}, author = {Madan, Mamta and Madan, Sushila}, volume = {6}, number = {4}, year = {2010}, month = {Apr}, pages = {413-416}, doi = {10.3844/jcssp.2010.413.416}, url = {https://thescipub.com/abstract/jcssp.2010.413.416}, abstract = {Problem statement: The purpose of this study was to describe categories of hybrid genetic algorithm and validate that the hybrid genetic algorithm converges to the optimal solution rather than a near optimal solution so that Hybrid Genetic algorithms can be used to solve real world problems and receive significant interest. Approach: We implemented the input allocation problem for a manufacturing unit firstly with pure genetic algorithm using Matlab's GA tool and then compared the results with hybrid genetic algorithm. Results: We observed that the results from applying only pure genetic algorithm to the problem were near optimal whereas when solved using hybrid genetic algorithm the results were significantly better and were optimal. Conclusion: The results presented by pure genetic algorithm and hybrid genetic algorithm are significant and validate that the hybrid genetic algorithm converges to the optimal solution rather than a near optimal solution. }, journal = {Journal of Computer Science}, publisher = {Science Publications} }