Relationship between Urban Transport and Residential Location Choice

This paper presents a fuzzy three-objective optimization model to study the relationship between residential location choice and urban transport in a city. In the proposed model, the fuzzy objectives are minimizing the family monthly variable money cost (including housing cost, management fee, living cost, traffic cost, and so on), minimizing one-way time cost per capita, and maximizing the housing condition. Three deterministic constraints are that the monthly family money cost and the one-way time cost per capita are less than family monthly disposable income and the upper limit of time-cost respectively, and that the monthly installment payment is not more than a fixed percentage of monthly disposable income. Furthermore, one fuzzy constraint is that the monthly family money cost is, if possible, not more than the budget. Compared with the existing models, the proposed fuzzy multiobjective optimization model contains the most factors and complex objectives; uses the monthly installment payment and rent as housing cost for buyers and renters, respectively; and divides the money cost and time cost into variable and fixed parts. Thus the proposed model is very close to the real world situation and is more accurate. The discrete uncertain distribution function and the membership function are constructed to describe the fuzzy data. Experimental results on a series of factual examples show that the proposed model and algorithm are reasonable and valid in predicting residential location choice. (C) 2018 American Society of Civil Engineers.