文章基本信息

标题：Robust Optimization Model Using Ellipsoidal and Polyhedral Uncertainty Sets for Spatial Land-Use Allocation Problem
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作者：Diah Chaerani ; Budi Nurani Ruchjana ; Putri Romhadhoni 等
期刊名称：Engineering Letters
印刷版ISSN：1816-093X
电子版ISSN：1816-0948
出版年度：2021
卷号：29
期号：3
页码：1220-1230
语种：English
出版社：Newswood Ltd
摘要：Land-use planning becomes an important thing todo because some land-use types can impact the environmentand life quality. Land-use planning is generally an activity thatinvolves the allocation of activities in a particular land. SpatialOptimization can be applied in land-use planning activity. Theoptimization model for the land-use allocation problem aims todetermine the percentage of land-use changes that can maximizethe comprehensive index and compactness index. In land-useplanning, there are several uncertainty factors. In this paper, therobust optimization model for the land-use allocation problem isdiscussed as a multi-objective function. There are two objectivefunctions to maximize the comprehensive index and to maximizethe density index. The uncertainties are assumed are in benefitand acquisition cost when a land planning is changed to anotherland-use type. In order to get a robust counterpart (RC)formulation, the uncertain parameter is assumed to lie withinan ellipsoidal and a polyhedral uncertainties set. A study forthe numerical experiment is done for Jatinangor District inKabupaten Sumedang, Indonesia, as an educational area. In thiscase study, two scenarios are discussed, i.e., the first scenarioallows a policy for changing all types of land to be other landtypes. The second scenario preserves a condition that a typeof land cannot be changed to another type. To handle themulti-objective optimization function, the lexicographic methodis employed. It is shown that the computational tractability ofthe RC is gained with ellipsoidal and polyhedral uncertaintyset. Thus, the robust optimal solutions are achieved.
关键词：robust optimization; spatial land-use allocation problem; ellipsoidal; polyhedral; uncertainty set