Research Of Product Line Planning Of Electronic Cigarette With Considering Market Factors

Compared with traditional cigarette,electronic cigarettes have the advantages of health,safety and convenience.They are favored by many domestic and international consumers at home and abroad.In recent years,the needs of electronic cigarette products have risen sharply in the market.Due to age,income,culture,habits and other factors,the consumer demands of electronic cigarette products are different.With the increasing attention to customer demands,managers of enterprises began to consider purchasing preference of different customers in the process of product line design optimization.Reasonable planning of product lines can not only attract different types of customer groups,but also expand the share of the market.At the same time,the similarity of the series of products in the product line can also reduce the cost of the product design and production process.Therefore,the positioning and planning of the electronic cigarette product line is very important for H enterprise to seize the opportunities and occupy the market share in the competition.The main research work includes the following three aspects:(1)The web crawler technology is used to capture product views,and word segmentation is used to analysis product views to get product features which are needed.The method of quality function deployment is used to implement the convention from customer demands to product attributes.(2)Product line optimization with considering market factors model is established.Part-worth utility values are used to express consumers' preferences of all the attribute levels and the utility of a product profile is assumed as a linear function of the part-worth utility values of the selected product attributes.Multinominal logit(MNL)customer choice rule which can avoid the shortcomings of traditional deterministic customer choice rule and more accurately describe customer purchase behavior is adopted in the optimization.(3)According to the characteristics of the established optimization model,genetic algorithm embedded with hill-climbing searching and tabu search algorithm are designed to solve the model and implemented with JAVA language.Finally,some related numerical experiments on the algorithm are performed based on the practical cases.The results of experiments are analyzed and summarized,which can provide some management insights for enterprises.The numeric experiments of the algorithms include parameter comparisons of genetic algorithm and tabu search algorithm and the contrast of two algorithms' optimization ability and the comparison of the algorithm optimization ability with embedded hill-climbing searching.