CHM-049 New Strategies Of Differential Evolution For Optimization Of Extraction Process

In recent years, evolutionary algorithms (EAs) have been applied to the solution of non-convex problems in many engineering applications. EAs differ from the conventional algorithms since, in general, only the information regarding the objective function is required. In the present work, a test problem on ‘optimization of extraction process’ is solved using Differential Evolution (DE) and two new DE strategies. The objective of the present study is to maximize the total extraction rate at constant disk rotation speed subject to the inequality constraints. In 1980, scientist used a modified gradient-projection technique and in 1989 GRG (generalized reduced gradient method) was used to solve this problem. Apart from the well known seventh strategy (DE-7) i.e., DE/rand/1/bin, the two new strategies (NS-1 & NS-2) have been applied. A comparison of DE-7 with the proposed two new DE strategies is presented. Experimental Simulations are carried out by running the code for all possible combination of the DE key parameters F & CR (0.0<F<=1; and 0.0<CR<=1.0), where F is scaling factor & CR is crossover constant. The proposed two new DE strategies found to be better and robust ensuring 100% convergence to the global optimum.