Urban layout optimization in a city network under an extended quadratic assignment problem framework

Abstract

For urban planning, transportation system in a region is essentially a result of the activity participation among geographically distributed locations. Facing congestion, pollution and other serious challenges, Metropolitan Planning Organizations (MPOs) need to offer effective decision-making supports to urban planning, especially urban layout optimization solutions. By mathematically defining the urban layout problem as a joint optimization of (a) activity space (AS)-to-location assignment, (b) demand distribution and (c) traffic flow assignment, this paper constructs an urban layout model by extending the quadratic assignment problem (QAP). In comparison with the standard model, our proposed framework considers possible flow distribution between different types of urban amenities, subject to the region-level demand control total constraint for certain activity types. A Maximal AS-to-location flow (MaxASLF) based heuristic algorithm and a Lagrangian relaxation-based approach are designed to solve the proposed models. Various examples and discussions are provided to examine the effectiveness of the proposed methods.