Research Of Integrating Supplier Selection Into Product Family Planning

With the economic globalization, the development cycle of products increasingly get shorter, more and more rich suppliers brought more and more fierce market competition, customers' needs turn to be personalized and diversified. The new dynamic environment makes mass customization to be the 21 st century mainstream production model.In new product development phase, product family technology has been considered as an effective method of achieving economies of scale and realizing mass customization production. At the same time, in order to adapt to the globalization of the competitive environment, to maintain low cost of production is one of the important challenges which the enterprises are facing. More and more companies have recognized that if suppliers participate jointly in the early stage of product development, both two sides will effectively save costs and increase the profit of the market, promote the product competitiveness in the market and increase customer satisfaction for the product.In this study, the research of integrating supplier selection into product family design can be summarized as the following aspects:First, the literature review. Related papers including the design of product family, selection of suppliers and product family design consideration of suppliers selection were reviewed and the problems to be studied are proposed.Second, establishment of optimization model. Supplier's influence in the early design of product family is considered. An optimization model integrating supplier selection into product family planning is established with an objective of maximizing the company's total profits. Customer's purchase behaviors, suppliers' expenses and outsourcing cost are considered in the model. The model uses probabilistic customer choice rules to simulate the customer selection behavior and to calculate product family expected market revenue.Third, design and implementation of the algorithms for solving the proposed model Genetic algorithm, tabu search algorithm and heuristic algorithm are designed and implemented with C++ language. The heuristic algorithm is embedded respectively in genetic algorithm and tabu search algorithm.Fourth, comparison of the algorithms and analysis of the sensitivity of model parameters. Application cases are given to perform the simulation study and sensitivity analysis, and to verify the feasibility of the proposed model and algorithms, Some insight are given from a management point of view. The algorithm experiments includes parameter comparisons of genetic algorithm and tabu search algorithm and the contrast of two algorithm's optimization ability and the comparison of the algorithm optimization ability with embedded heuristic algorithm. The model simulation experiment includes parameter sensitivity analysis of the cost of suppliers, suppliers quantity, product variant number top limit which product family includes, the price of the product variant as well as comparison of deterministic choice model and probabilistic choice model.