Optimization and Control of the Urban Spatial Dynamics

Abstract

Urban planning involves the assignment of land use to each land cell. This process coexists and may conflict with the complex self-organized dynamics of the urban system, which should be constrained by the plan. The purpose of this study is the identification of a method for attaining the planned goals through the utilization of the self-organized dynamics, and the minimization of the constraints. The paper is organized in three steps. First, the urban plan is defined as a process of optimization. Second, the set of optimal solutions is compared with the configurations resulting by the self-organized dynamics. Third, a method for the convergence of the self-organized dynamics with the optimal configuration is proposed. In conclusion, the study shows that planning a complex system may be a hard task, while the control and the utilization of the self-organized dynamics help in the attainment of a total utility.

Generating Alternative Land‐use Allocation for Mixed Use Areas: Multi‐Objective Optimization Approach

“…These heuristic approaches allow trade‐off between the quality of solution and the burden of computation, and hence is often used to find a near‐optimal solutions (Laarhoven and Aarts ). Semboloni () used simulated annealing (SA) to optimize the facilities required for residential and commercial areas. Shifa et al () applied particle swarm optimization (PSO) to optimize the allocation of land‐uses, considering maximum suitability of land and a minimum cost of changing the land shape.…”