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Multi-Objective Evolutionary Computation Solution for Chocolate Production System Using Pareto Method

Solving manufacturing engineering problems normally involves variety of challenges. It is important to maximize profit, improve quality of a product mean while reduce losses and cost. This trade-off plays a vita role in solving many manufacturing optimization problem. The Chocoman Inc, USA produces varieties of chocolate bars, candy and wafer by means of raw materials. The objective of the company is to minimize its cost while maximizing the production of eight products. The formulation of this problem resulted in five functions to be optimized based twenty nine constraints to be satisfied. This is a typical Multi-objective Optimization Problems (MOPs). Many methods attempted to solve this problem. In this paper, we provide a comparison between the Scalarization and Pareto methods based Genetic Algorithms (GAs) to solve the chocolate production problem. GAs provides an outstanding solution.