In facilities location planning various location models to support decision-making have been proposed. Many of them assume that every resident uses only one facility, however, in reality, especially in the case of commercial facilities, they use many facilities selectively and total amount of realized demand varies, according to both location and attractiveness of facilities. Thus, a new location model that considers elasticity of demand is needed. Non-constraint type of Spatial Interaction Model (SIM) by A.G. Wilson considers elasticity of Demand. In the model, amount of Realized Demand is formulated to increase unlimitedly in proportion to Potential Demand and Supply Level. However, in reality, Realized Demand doesn't increase unlimitedly, because elasticity of demand is not infinite. In this point, non-constraint type of SIM doesn't correspond to the reality. Firstly, in this paper, a new criterion of Maximum Realized Demand is presented, and new SIM developed from non-constraint type of SIM is presented. Newly introduced criterion: Maximum Realized Demand, can be called "estimated maximum value of Realized Demand". Realized Demand never exceeds Maximum Realized Demand. And a new location-optimizing model to maximize sum of Realized Demand (e.g. total amount of visitors to facilities) based on new SIM that uses above-stated new criterion is proposed. Also a heuristic method of solution is shown. Validity of this method is confirmed by comparison with combinatorial method of optimization. In order to investigate new location model, three kinds of simulations on optimal location are shown.
1. Simulations on two different demand distributions and two different values of b. Through simulation, it is cleared that optimal location is very sensitive to configuration of demand distribution and parameter b.
2. Simulations on different numbers of facilities. When number of facilities is small, facilities optimally locates around center of domain. But as number of facilities increases, optimal location is getting away from center, and location becomes like a ring or a doughnut. This tendency corresponds to processes of actual city growth.
3. Simulations on different values of Maximum Realized Demand. In the case of public facilities, equality of Supply Level also must be considered. So, through this simulation, adaptability to public facilities location problem is investigated. It is shown that as Maximum Realized Demand is set lower optimal location is getting away from center and field of supply level is getting flatter (equal for residents). As a result, it is suggested that this presented location model is also useful for public facilities location planning as well as commercial and private facilities location planning.
Through simulations, many characteristics of presented location model are cleared. Consequently, it is confirmed that presented model is very exquisite and may be able to explain the system of city too. Furthermore, validity of presented model as a Decision Support System for both public facilities and private facilities location is suggested.