Published Paper Details:

Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum regardless of the initial parameter values, fast convergence, and using few control parameters. The biggest advantage of the differential evolution approach over other non-traditional method approach is its stability. DE algorithm is a population based algorithm like genetic algorithms using similar operators; crossover, mutation and selection. Differential evolution algorithm can be easily applied to a wide variety of real valued problems despite noisy, multimodal, multidimensional spaces which usually makes the problems very difficult for optimization. Differential evolution becomes impressive because of the parameters crossover ratio (CR) and mutation factor (F) do not require the same tuning which is necessary in many other Evolutionary Algorithms. In the present study, DE has been used to solve the various chemical engineering problems from the literature. We have compared the performance of DE algorithm to that of some other well-known versions conventional and non-conventional optimization methods. From the simulation results, it was observed that the convergence speed of DE is significantly better than the other techniques. Therefore, DE algorithm seems to be a promising approach for engineering optimization problems.