The widespread use of the Internet has significantly changed the behavior of homebuyers. Using information technology, homebuyers can rapidly find an appropriate house that meets their needs. Although online real estate agents can screen out first based on homebuyers’ requirements, however, most of current online housing systems are of limited abilities, particularly without considering homebuyers’ housing goals and risk attitudes. To increase effectiveness, online real estate agents should provide an efficient matching mechanism, personalized service and house ranking with the aim of increasing both buyers’ satisfaction and ideal rate. An efficient matching mechanism should provide an easy way for homebuyers to find a suitable house with consideration of their different housing philosophies and risk attitudes. In order to comprehend these ambiguous housing goals and risk attitudes, it is also indispensable to determine a satisfaction level for each fuzzy goal and constraint.

In this study, we propose fuzzy goal programming with an S-shaped utility function as a decision aid to help homebuyers choosing the preferred house via Internet. Homebuyers can specify their housing constraints with different priority levels and the thresholds for fuzzy search that can translate into standard query language for a regular relational database.