Locating Street Markets: Analysis from qualitative and quantitative factors using a discrete choice model, Mixed Integer Nonlinear Programmingand Fuzzy AHP

Street markets can play a key role in addressing food insecurity and promoting equitable access to nutritious food, particularly in urban areas where food deserts are common. Their strategic location could enhance their sustainability and positive impact on urban communities. Despite their potential, previous studies have rarely integrated urban planning constraints with mathematical optimization models for street market locations such as population density, land use regulations, accessibility, and transport infrastructure. This gap limits the ability to effectively combine qualitative and quantitative factors in street market planning. This paper presents a mathematical model combining Mixed Integer Non-Linear Programming (MINLP) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) to determine the optimal locations for street markets. The objective is to integrate demand, distance, urban regulations, and community needs into a decision-making framework. The model was applied to the district of Bosa in Bogotá, Colombia, using geospatial data and urban planning criteria. Factors such as population density, road infrastructure, and zoning regulations were considered. The Fuzzy AHP incorporated expert opinions, while the MINLP addressed real-world constraints such as buffer zones and customer accessibility