Optimal Design and Process of Threshing Units Based on a Genetic Algorithm. I. Algorithm

This paper concludes with the formulation of a multiobjective genetic algorithm for optimization of design and functional parameters of threshing units. This approach implied the blending of performant, reliable mathematical models that describe the whole process and an evolutionary search method (a genetic algorithm in relationship with fuzzy logic). Design and operation parameters in connection with physical properties of a certain crop are expressed as variables of a complex, constrained, nonlinear, multiobjective problem. Solving the problem requires finding the setting of above-mentioned decision variables, so that an evaluation function based on process quality criteria is maximized. To solve the problem at hand a genetic algorithm is implemented. Improvements of the algorithm performance are obtained using elitist selection strategy and selective weights in the evaluation function. Once this successful evolutionary computation approach has been developed, it can be incrementally adapted to other threshing units in various crops.