Spatial Decision Support System for Efficient School Location-Allocation

Abstract

In Greece, a lack of a planning strategy was identified in the context of allocating students to schools. Particularly, the Secondary Educational Management of Lesvos Prefecture along with school Principals decide upon student allocation based on empirical knowledge and approximation techniques. As a consequence, during the school season of 2018-2019 capacity and proximity limitations were violated. This study introduces a Spatial Decision Support System (SDSS) to assist school location-allocation decisions in future seasons. The objective of the proposed SDSS is to minimize commute-to-school distance concerning capacity and proximity limitations. For this purpose, a capacitated P-median approach is adopted and formulated as a mixed-integer linear problem. The SDSS is further evaluated using actual data for students' transition from primary to secondary education in the city of Mytilene, Greece. Evaluation of current allocation practices carried out and further compared to those obtained by the SDSS. The results indicate a decrease of 8% in total distance whereas proximity and capacity constraints were respected accordingly. The results may be potentially useful for school planners to assist the allocation decisions in the city of Mytilene.

Kajian Karakteristik Lahan Untuk Mendukung Penyusunan Model Decision Support System (Dss) Optimalisasi Lahan Di Kabupaten Pangkep

“…Pengembangan telah dilakukan oleh (Brown et al, 2005) yang mengembangkan SDSS untuk peningkatan produksi di lahan tropis dan (Churi et al, 2013) yang mengembangkan SDSS untuk peningkatan produksi tanaman di wilayah semiarid (De La Rosa et al, 1999;Virgil, 1998;dan Kiong Siew Wai et al, 2005) juga menggunakan SDSS untuk pengembangan manajemen lahan. SDSS juga diaplikasikan pada bidang lain seperti bidang kesehatan (De Lima et al, 2019;Yu Lan et al, 2020), dan bidang pendidikan (Batsaris et al, 2021;Eremeev et al, 2022).…”

Building a spatial decision support system for tourism and infrastructure planning: technical solution and data integration challenges

“…Based on the literature on SDSS, it can be concluded that these systems are often tailored for one specific task and deploy a specific set of analytical capabilities. Some of them use multi-criteria analysis (Jeong & Ramírez-Gómez, 2018;Maleki et al, 2018), while others include spatial statistics to find hotspots or optimal locations based on location-allocation models (Yeh & Chow,1996;Tavana et al, 2017;Arentze et al,2020Dell'Ovo et al 2020, Sakellariou, et al 2020Batsaris et al, 2021). To produce a more generic SDSS that can be used in spatial planning such as a mobility gap-analysis, greater flexibility, both in terms of available methods but also in terms of integrating multiple data sources, has to be implemented.…”

Towards a similarity index of network paths in spatial networks

“…In general, this can also include the study of cities or geographical areas from a sustainable development perspective, especially if we are concerned with public service provision and equity of service delivery (Boeing, 2022). Batsaris et al (2021) developed a Spatial Decision Support System (SDSS) to minimise school travel by combining shortest path algorithms on road networks and location assignment analysis. Paraskevopoulos et al (2019) describes how the degree of connectivity in a spatial network affects spatial relationships and contributes to the calculation of population accessibility in island settlements for tourism development.…”