This article presents the development and application of a methodology that employs optimization not to seek the single or few optimal plan(s) but to provide planners with a systematic overview of their decision space. As urban development projects are not only subject to decisions of planners but also to those of many actors, the insight about how different actors would decide based on the decisions of the planners should enable planners to already adapt their decisions to ensure that final project targets are reached. The existence of different decision makers is considered via a multiparametric mixed-integer linear programming (mpMILP) approach. Along with the methodology a model was developed, which incorporates multiple domains and scales. Those domains include social, environmental, form, energy, and economic aspects. The considered scales range from single floors up to a neighborhood. Model and methodology were applied to a greenfield development project. Two practical questions are answered, which address the impact of planning decisions about (a) the building density and the sustainability of the energy supply on costs of different actors and (b) the building density and the share of parks on the view on a landmark. The capturing of the decision space revealed trade-offs in terms of chosen energy supply system and urban form, respectively. The presented computational method forms part of the decision support tool URBio, which shall assist urban planning.