On the Morphology of a Growing City: A Heuristic Experiment Merging Static Economics with Dynamic Geography
نویسندگان
چکیده
In this paper, we aim at exploring how individual location decisions affect the shape of a growing city and, more precisely, how they may add up to a configuration that diverges from equilibrium configurations formulated ex-ante. To do so, we provide a two-sector city model merging a static equilibrium analysis with agent-based simulations. Results show that under strong agglomeration effects, urban development is monotonic and ends up with circular, monocentric long-term configurations. For low agglomeration effects however, elongated and multicentric urban configurations may emerge. The occurrence and underlying dynamics of these configurations are also discussed regarding commuting costs and the distance-decay of agglomeration economies between firms. To sum up, our paper warns urban planning policy makers against the difference that may stand between appropriate long-term perspectives, represented here by analytic equilibrium configurations, and short-term urban configurations, simulated here by a multi-agent system.
منابع مشابه
A Framework for Adapting Population-Based and Heuristic Algorithms for Dynamic Optimization Problems
In this paper, a general framework was presented to boost heuristic optimization algorithms based on swarm intelligence from static to dynamic environments. Regarding the problems of dynamic optimization as opposed to static environments, evaluation function or constraints change in the time and hence place of optimization. The subject matter of the framework is based on the variability of the ...
متن کاملتأثیر هشت هفته تمرینات منتخب تایچی بر تعادل ایستا و پویای زنان مبتلا به مالتیپلاسکلروزیس با تأکید بر تیپ بدنی مزومورف و اندومورف (تحقیق کارآزمایی بالینی)
Background and Objective: Different morphologies are factors for the effectiveness of training programs on subjects. The aim of this study was the effect of 8-week Tai Chi exercise on static and dynamic balance in women with multiple sclerosis (MS) with emphasis on mesomorph and endomorph's morphology. Materials and Methods: In a clinical trial, 48 patients with MS were purposefully select...
متن کاملSTATIC AND DYNAMIC OPPOSITION-BASED LEARNING FOR COLLIDING BODIES OPTIMIZATION
Opposition-based learning was first introduced as a solution for machine learning; however, it is being extended to other artificial intelligence and soft computing fields including meta-heuristic optimization. It not only utilizes an estimate of a solution but also enters its counter-part information into the search process. The present work applies such an approach to Colliding Bodies Optimiz...
متن کاملIntroducing a new meta-heuristic algorithm based on See-See Partridge Chicks Optimization to solve dynamic optimization problems
The SSPCO (See-See Particle Chicks Optimization) is a type of swarm intelligence algorithm derived from the behavior of See-See Partridge. Although efficiency of this algorithm has been proven for solving static optimization problems, it has not yet been tested to solve dynamic optimization problems. Due to the nature of NP-Hard dynamic problems, this algorithm alone is not able to solve such o...
متن کاملPerformance Analysis of Dynamic and Static Facility Layouts in a Stochastic Environment
In this paper, to cope with the stochastic dynamic (or multi-period) problem, two new quadratic assignment-based mathematical models corresponding to the dynamic and static approaches are developed. The product demands are presumed to be dependent uncertain variables with normal distribution having known expectation, variance, and covariance that change from one period to the next one, randomly...
متن کامل