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Two alternative methodological approaches (the IPFP based and the intramax procedures) to the problem of pattern identification in spatial interaction data are compared and evaluated in this paper. After a general discussion of the major characteristics and shortcomings of these methodologies, the paper presents the findings of a case study relying on telecommunication data measured by the Austrian PTT in 1991, in terms of erlangs. The results clearly illustrate the superiority of the intramax approach in the context of mediumsized and relatively centralised flow systems. (authors' abstract)

Research in the area of spatial decision support (SDS) and resource allocation has recently generated increased attention for integrating optimization techniques with GIS. In this paper we address the use of spatial optimization techniques for solving multi-site land-use allocation (MLUA) problems, where MLUA refers to the optimal allocation of multiple sites of different land uses to an area. We solve an MLUA problem using four different integer programs (IP), of which three are linear integer programs. The IPs are formulated for a raster-based GIS environment and are designed to minimize development costs and to maximize compactness of the allocated land use. The preference for either minimizing costs or maximizing compactness has been made operational by including a weighting factor. The IPs are evaluated on their speed and their efficacy for handling large databases. All four IPs yielded the optimal solution within a reasonable amount of time, for an area of 8 × 8 cells. The fastest model was successfully applied to a case study involving an area of 30 × 30 cells. The case study demonstrates the practical use of linear IPs for spatial decision support issues.

The method of hierarchical information integration can be applied to the study of complex decision-making processes in which preference formation is influenced by many attributes of choice alternatives. In this paper, we extend Louviere's (1984) original approach to include the modeling choice processes in addition to judgment processes. Assumptions underlying the original and our extension are discussed and the new method is applied in an analysis of residential choice behavior.

There are still only a few operational models of pedestrian movement. In particular, the gravity /entropy-maximizing model has received most attention. In this paper a descriptive model of pedestrian movement is presented. It can be considered as an extension of O'Kelly's model of the demand for retail facilities in the presence of multistop, multipurpose trips. The model basically consists of three submodels: one for destination choice, one for route choice, and one for impulse stops. Together, these submodels describe/predict the total demand for retail facilities within inner-city shopping areas. The model is applied to data from the city of Maastricht, The Netherlands.