资源环境科技发展态势分析平台

Because the social benefit generated from a public facility varies according to its accessibility, population density of location, local income level, local taste, and the existence of similar nearby facilities, the value of facilities can vary depending on their location. Therefore, determining the ideal location is an important problem. This study provides a new direction for solving this problem by combining the contingent valuation (CV) method and nested partitions (NP) algorithm using siting of public arboretums as an example. First, consumers' willingness to pay for environmental facilities considering household characteristics and distance to both newly built and existing facilities are estimated using the CV method. In this process, consumers are divided into two groups (active and passive users), assuming they have different willingness to pay for the facilities. Then, using the results of the CV, the NP algorithm, a simulation-based discrete optimization technique, is constructed to efficiently identify optimal locations that maximize social benefit considering regional characteristics. The results of the proposed algorithm exceeded the performance of the benchmark case, and this study's findings can be used to aid decisions about complicated multiple facility locations. Moreover, visualized results are provided, which can be useful for local and central decision makers.