| With the rapid development of economy and globalization,competition among enterprises is more and more fierce,product life cycle is also gradually reduced and consumer demand trend to be variant and diverse.In order to occupy market share in the fierce competition,enterprises have to design the product to satisfy diverse consumers.Therefore,customer is a vital element in the relationship of supply-demand.More and more enterprises turn to be customer-focus and design reasonable product line to produce more diverse product categories to cater to consumers,and then enterprises can expand market share and increase profits.In the process of product line design,the result of product line optimization design is severely affected by customers’ utilities towards a product.Random utility model is always used to solve product line problem,but the model depends on a hypothesis that all random error mutually keep independent and identically distributed.Therefore,the hypothesis is too strong to ensure.In this thesis,utility is regarded as a fuzzy number to accurately describe consumer preference.The thesis proposes product line design based on fuzzy utility,and tries to improve the description of preference to better guide the product line decision-making to expand the market share of enterprises,increase profits,and ultimately enhance the market competitiveness of enterprises.The main work includes the following aspects:(1)Market share is an important indicator for enterprises,and it reflects how many consumers prefer to select these products.So this thesis uses two-step method to establish the product line optimization model based on fuzzy utility to realize maximum market share,then the nonlinear model is linearized to get the optimal solution by Cplex.In addition,the thesis designs an improved bacterial foraging optimization algorithm to solve the model with large scale in practice.(2)The ultimate purpose of enterprises participating in competition is to make more profit.This thesis establishs a product line model based on fuzzy utility by two-step method with the objective of maximizing profit.The nonlinear model is linearized to persuit exact solution.Similar to the proposed algorithm in section 3,the thesis designs an improved bacterial foraging optimization algorithm for the profit model.(3)Three scenarios are considered in the case library to create experimental data.In the stage of experiment,this thesis compares the exact solutions with optimal solutions of heuristic algorithms with smaller-scale data.It verifies the correctness of linearized models and proposed algorithms.In addition,because the large-scale data is beyond the Cplex’s ability to solve,this thesis evaluates the results by some indices to validate the stability and effectiveness of the proposed algorithms. |
