To Build or Not To Build: Determining a Quantitative Metric for Land Planning and Allocation

Zixuan Li, Yan Xiao, Ziang Li, Jocelyn Wang
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Abstract

Land planning is crucial to ensure that urban development occurs with consideration to the economic, social, and environmental interests of a community. Many conflicting factors must often be considered to adhere to optimal land planning. In this paper, our team makes a quantitative decision metric that can analyze these factors and determine the “best” choice from a given set of development options and the allocation of those choices. First, linear programming is used to determine two “best” development options: one that maximizes both economic and social factors and one that minimizes negative environmental factors while maximizing social. The maxima and minima from linear programming are then applied to the Technique for Order of Preference by Similarity to the Ideal Solution to obtain a third real-world “overall best” option that balances economic and environmental factors with a desired weighting. A genetic algorithm is then used to determine the optimal positioning of the three established “bests” by analyzing opportunity costs based on an environmental degradation penalty index. Finally, the Cobb-Douglas Function is used to conduct a short- and long-term analysis of each result’s profit by solving differential equations about inflation. This model is then applied to the parcel of land in Victory, NY, using data obtained from research. The ideal option and positioning are found to be 267 acres of a sports complex in the northern half of the land, 129 acres of regenerative farm directly west of the sports complex, 344 acres of a solar array in the southernmost region of the land, and 1 acre of agritourism center on the eastern side of the land. Conducting a sensitivity analysis on our model reveals that the linear programming results are most affected by the area and societal benefit restrictions but that the TOPSIS results remain relatively stable regardless of the changing parameters. Our model is adjusted to account for Micron Technology, Inc. building a nearby fabrication facility. As this facility brings more jobs and thus more people, the profit of facilities that involve tourism will increase. However, nature-based facilities will suffer detriment due to pollution caused by the facility. With these adjustments, the model is re-run, and the results are compared to the previous results. In this scenario, there would be a greater area of the solar array and agritourist center, a smaller sports complex, no regenerative farm, and 128 acres of ranch. Finally, the generalizability of our model is discussed by first discussing its application in Shenzhen, China, and then widening the scope to any location in any country. Our model will provide the most implementable results in rural environments due to its quantitative nature that cannot consider complicated urban planning laws but that the model can be applied to nearly any scenario as long as data is provided.
建还是不建:确定土地规划和分配的定量指标
土地规划对于确保城市发展考虑到社区的经济、社会和环境利益至关重要。为了坚持最佳的土地规划,必须经常考虑许多相互矛盾的因素。在本文中,我们的团队制定了一个定量决策度量,可以分析这些因素,并从一组给定的开发选项和这些选择的分配中确定“最佳”选择。首先,线性规划用于确定两个“最佳”发展选择:一个是将经济和社会因素最大化,另一个是将负面环境因素最小化,同时将社会因素最大化。然后将线性规划中的最大值和最小值应用于与理想解决方案相似的偏好排序技术,以获得第三个现实世界的“整体最佳”选项,该选项以期望的权重平衡经济和环境因素。然后使用遗传算法通过分析基于环境退化惩罚指数的机会成本来确定三个已建立的“最佳”的最佳定位。最后,通过求解有关通货膨胀的微分方程,利用科布-道格拉斯函数对每个结果的利润进行短期和长期分析。然后,使用从研究中获得的数据,将该模型应用于纽约州胜利的一块土地。理想的选择和定位是在土地的北半部有267英亩的体育综合体,在体育综合体的正西有129英亩的可再生农场,在土地的最南端有344英亩的太阳能电池阵列,在土地的东侧有1英亩的农业旅游中心。对模型的敏感性分析表明,线性规划结果受区域和社会效益限制的影响最大,但无论参数如何变化,TOPSIS结果都保持相对稳定。我们的模型进行了调整,以考虑到美光科技公司(Micron Technology, Inc.)在附近建造的制造工厂。随着这个设施带来更多的就业机会,从而带来更多的人,涉及旅游的设施的利润将会增加。然而,基于自然的设施将受到损害,因为设施造成的污染。通过这些调整,重新运行模型,并将结果与之前的结果进行比较。在这种情况下,将会有一个更大的太阳能电池阵列和农业旅游中心,一个较小的体育中心,没有可再生农场和128英亩的牧场。最后,本文首先讨论了该模型在中国深圳的应用,然后将其范围扩大到任何国家的任何地点。我们的模型将在农村环境中提供最可实施的结果,因为它的定量性质不能考虑复杂的城市规划法律,但只要提供数据,该模型几乎可以应用于任何场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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