Balancing the Portfolio of Urban and Public Projects with Distance-Dependent Coverage Facilities

Abstract

The portfolio of urban and public projects should be balanced in terms of completion time, districts and strategic objectives. For this purpose, we suggest a mixed integer nonlinear programming model based on the goal programming approach. Projects are selected so as to minimize the squared deviation of urban and regional development indicators from their respective targets. In the proposed model there are two category of indicators: coverage indicators that are measured based on the distance of each neighborhood from the nearest covering facility, and general indicators that are usually measured based on the capacities and capabilities of each district. It is assumed that the location of covering facilities have already been selected, but the construction of these facilities will be prioritized and planned according to budget constraints and in competition with other regional development projects. Numerical results indicate superior performance of proposed genetic algorithm in comparison to GAMS solvers. Finally, the application of the model is illustrated by an example.