토지 획득 문제에서 공간적 밀집도 측정을 위한 최적화 연구

An Optimization Approach for a Spanning Tree-Based Compactness Measure in Contiguous Land Acquisition Problems

  • 투고 : 2011.09.01
  • 심사 : 2011.12.22
  • 발행 : 2011.12.31

초록

토지 획득 문제(land acquisition problems)란 일련의 목적에 맞게 서로 인접하고 있는 최적의 토지 필지들을 찾는 것이다. 이 문제는 도시 및 지역 계획과 각종 구획 문제 등에서 사회적 활용도가 높은 분야로서, 공간적 요소인 인접성(contiguity)와 밀집도(compactness)는 중요한 제약요소로 다루어지고 있다. 그렇지만, 공간적 밀집도(spatial compactness)는 완벽한 측정방법이 존재하지 않고, 획득된 필지들의 둘레를 제거나, 모양을 측정하는 등의 여러 가지 방법으로 측정되고 있다. 그리하여 이 논문에서는 공간적 밀집도를 측정하는 새로운 방법을 제시하고자 한다. 인접한 토지 필지간의 내부적인 구조적 특징을 바탕으로 proximity degree라고 불리는 공간적 밀집도를 측정하는 최적화 연구모델(optimization model)을 발전시켰다. 일련의 실험을 통해 proximity degree에 따라 다양한 공간적 밀집도를 가진 모습을 확인할 수 있다.

The goal of solving a contiguous land acquisition problem is to find an optimal cluster of land parcels so that one can move from an acquired parcel to another without leaving the cluster. In many urban and regional planning applications, criteria such as acquisition cost and compactness of acquired parcels are important. Recent research has demonstrated that spatial contiguity can be formulated in a mixed integer programming framework. Spatial compactness, however, is typically formulated in an approximate manner using parameters such as external border length or other shape indices of acquired land parcels. This paper first develops an alternative measure of spatial compactness utilizing the characteristics of the internal structure of a contiguous set of land parcels and then incorporates this new measure into a mixed integer program of contiguous land acquisition problems. A set of computational experiments are designed to demonstrate the use of our model in a land acquisition context.

키워드

참고문헌

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