Entropy‐Based Spatial Interaction Models for Trip Distribution. 基于熵的空间相互作用模型在出行分布中的应用

Abstract

Wilson's use of entropy‐maximization techniques to derive a family of spatial interaction models was a major innovation in urban and regional modeling. The work elegantly linked methods for transportation analysis and regional economics into a unified framework. One version, the doubly constrained spatial interaction model, is closely related to the transportation problem of linear programming and other existing trip distribution techniques. This article traces some of these connections, particularly the sense in which an entropy model with an average trip length constraint can be seen as a relaxation of a least cost solution to a linear program. These ideas have renewed significance in the context of studies of simulation models for regional economies. Wilson's developments therefore provided a unifying basis for the work of very creative urban and regional modelers of that time (e.g., Alonso, Batty, Evans, Harris, Herbert, Lakshmanan, Stevens, Webber) and indicate the lasting and significant influence of his insight.