Product Line Design Optimization Based on Fuzzy Utility

With the deepening of globalization, competition in the new market environment is becoming increasingly fierce, and the product life cycle is gradually shortened, as a result, customer demand becomes diversifying and differentiating. To expand market share, companies have to design a series of new products to meet various demands so that can survive in the fierce competition and rapid development. To closely describe customers' satisfaction, it is regarded as a fuzzy number to reflect the uncertainty of customers' preferences. Therefore, product line design based on fuzzy utility is proposed to better guide decision-making to expand the market share of enterprises, and ultimately enhance the market competitiveness of enterprises. In this research, the goal of maximizing market share has been established by the two-step method which is a classical method of a product line optimization method, and a nonlinear model is linearized by adding some middle variables to solve the exact solution of the problem. However, the exact solution is limited by the size of the problem, due to the larger scale in practice. We design an improved bacterial foraging optimization that combines genetic operators to solve large-scale problems. In the stage of experimental design, the correctness of the algorithm is verified by comparing exact solutions with optimal solutions with small-scale data. In addition, some larger-scale experiments confirm the versatility and stability of the algorithm.