spopt: a python package for solving spatial optimization problems in PySAL

Abstract

Spatial optimization is a major spatial analytical tool in management and planning, the significance of which cannot be overstated.Spatial optimization models play an important role in designing and managing effective and efficient service systems such as transportation, education, public health, environmental protection, and commercial investment among others.To this end, spopt (spatial optimization) is under active development for the inclusion of newly proposed models and methods for regionalization, facility location, and transportation-oriented solutions (Feng et al., 2021).Spopt is a submodule in the open-source spatial analysis library PySAL (Python Spatial Analysis Library) founded by Dr. Sergio J. Rey and Dr. Luc Anselin in 2005(Rey et al., 2015, 2021;;Rey & Anselin, 2007).The goal of developing spopt is to provide management and decision-making support to all relevant practitioners and to further promote the appropriate and meaningful application of spatial optimization models in practice. Statement of needSpatial optimization methods and algorithms can be accessed in many ways.ArcGIS 1 and TransCAD 2 are two well-known commercial GIS software packages that provide modules designed for structuring and solving spatial optimization problems.The optimization functions they offer focus on a set classical single facility location methods (e.g., Weber, Median, Centroid, 1-center), routing and shortest path methods (e.g., shortest path on the network, least cost path over the terrain), and multi-facility location-allocation methods (e.g., coverage models, p-median problem).They are user-friendly and visually appealing, but the cost is relatively high (Murray, 2021).Open-source software is another option to access spatial optimization.Although it may require users to have a certain level of programming experience, open-source software provides relatively novel and comprehensive methods, and more importantly, it is free and can be easily replicated.This is particularly true for regionalization and facility-location methods.Regionalization methods are limited in commercial GIS software, and may only have grouping analysis for vector data and region identification for raster data.On the contrary, there are many application-oriented open-source packages that facilitate the implementation of regionalization methods in various fields, including climate (e.g., HiClimR (Badr et al., 2015), synoptReg

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