GA-simplex algorithm and its application: A case study of gas emission estimation

Among the mathematical optimization algorithms, simplex algorithm is a popular and practical algorithm which was listed as one of the top 10 algorithms of the twentieth century by the journal Computing in Science and Engineering. Although simplex algorithm is efficient in the linear programming, the quality of convergence is unacceptable in practice as a numerical breakdown of the algorithm, even for smooth and well-behaved functions. On the other hand, full convergence might be seen in genetic algorithms (GA) using only crossover. So in this paper we combine the GA and simplex algorithm by initializing simplex from the final individual in GA and getting the converged result through simplex algorithm thereafter. A case study in estimating gas emission shows noteworthy improvement of efficiency and stability, compared with GA or simplex algorithm.