近年来,中国电子商务产业发展迅猛,电商平台上的海量信息为消费者提供更多购物选择的同时,也极大地增加了消费者实现最优购物决策的难度.文章提出了一种模拟消费者在电商平台上实现最优购物决策的方案------基于Vague集的两阶段模糊决策算法,模拟了消费者网购过程中的搜索路径,并最终得到最优购买决策方案.该算法首先根据目标商品的价格和质量特征对目标商品进行分类,并运用DEMATEL方法完成不同类别商品的统一化处理;然后,以消费者购物时最关心的商品价格和质量两个方面为切入点对消费者进行分类,并据此得到消费者对目标商品价格偏好系数的取值;最终, 通过对传统的理想点算法进行改进,提出一套完整可行的多目标模糊算法,模拟消费者实现最优网购决策.在算法实证中,选取典型的代表性商品进行算法检验, 证明了该算法的可行性及其有效性.相较于以往的研究,文章给出的算法适用于模拟各类消费者在电商平台上的购物决策, 为消费者在海量信息的电商平台上实现更高效的购物策略选择提供了有效的参考.

This article was written based on the background of the development of e-commerce to discusses the simulation of the electric business platform shopping decisions significance and feasibility using Vague set of fuzzy theory. There are two stages of fuzzy decision algorithm. First, according to the target prices of the goods and quality characteristics of target commodity classification, by using DEMATEL method it complete the transformation of different categories of goods innovatively. Second, classify consumers based on commodity prices and quality which consumers mostly care about, by doing it you can put forward the consumer preference coefficient of the target price. You can combine the ideal point method, and put forward a multi-objective fuzzy algorithm which is more fit to consumption decision. In the algorithm the empirical, selecting typical algorithms on behalf of commodity inspection, prove the feasibility and effectiveness of proposed algorithm. Compared with previous studies, the algorithm this paper presents is suitable for the simulation of various types of consumer shopping decisions on electric business platform.