and Game Theory: An Article Review
Full Bibliographic Reference
Liu, Y., Tang, W., He, J., Liu, Y., Ai, T., & Liu, D. (2015). A land-use spatial optimization model based on genetic optimization and game theory. Computers, Environment, and Urban Systems, 49, 1-14.
Introduction
Objectives and Article Domain
Considering the scarcity of land in the present time, it is important to strategize land usage to achieve the desired economic outcomes using the available land. As such, it is important to compact the land in order to maximize its economic use. In response to this problem, the article aimed to determine the land-use sustainability and compactness using the landscape shape index. The scope of the article includes topic areas which are related to land use competition and spatial optimization, as well as genetic algorithm and game theory.
Intended Audience and Appropriateness of the Journal
The article is intended for both the academic and the practical communities. This means that land experts from the academe are able to review the underlying theories behind the proposed model and be able to make suggestions for further improvements. On the other side, practical applications of the model might be considered as readers from different sectors of society. Furthermore, businesspersons, agriculturists, engineers, and land-use economists might be able to benefit with this proposed model. As far as the journal is concerned, The Computers, Environment, and Urban Systems journal is an appropriate journal for the article since it is a scientific research and intended towards future development of urban systems. Furthermore, the article considers the conservation of environmental resources, particularly the land, because optimizing land usage will help in the reduction of the unnecessary spaces; therefore, it is convenient for people in the Gaoqiao Town (the place where the study will commence) to find more opportunities regarding land usage.
Article Classification
The article used field and case studies to gather the needed data for variables such as land usage and compactness. Equations are also provided instead of conceptual ideas and the use of logical reasoning to analyze the gathered data. Also, the article is not one-sided and makes the readers support the details in it. Because of the use of the experimental approach and statistical analysis to meet its objectives, the article is considered to be empirical in nature.
Brief Summary
Maximizing the land use for different purposes is a current problem especially in areas where there are many potential lands that can be converted into many different facilities. As a response for this on-going problem, many researchers proposed different land-use optimization models to help maximize the efficiency of the spaces. Among the recent solutions pertaining to this issue on land usage is the genetic optimization model and the game theory (Liu et al., 2015).
A genetic optimization model infused with the theoretical foundations of the game theory enables researchers to continuously search for the most suitable layout of land usage. Genetic mechanism is responsible for finding patterns of land usage, which is helpful in finding the best position to situate future establishment relative to its potential competitors, Meanwhile, game theory proposed strategies for an effective negotiation between land users (such as farmers) and the local government to make sure that the competition and land use allocation will be fair and the two parties would reach a certain agreement. With this model, not only the issues of land use are being addressed, but also the fair competition among establishments (Liu et al., 2015).
Results
The result of the field study in Gaoqiao Town confirmed that the model is suitable for land-use optimization with regards to the multiple activities that are facilitated within the location. Furthermore, the competition among land users can also be identified and they can be subjected to coordination for the purpose of being fair with the other competitors (Liu et al., 2015). Results implied that land-use optimization is a potential strategy to ensure a fair competition among establishments.
Contributions
The article discussed a new approach in land-use optimization. For a long time, land-use optimization is a problem in many places all over the world since spaces are being occupied as time goes by, which leads to the idea that there will be an unequal distribution of development and environmental lands in the upcoming year (Meyer, Lescot, & Laplana, 2009). The article contributed a new way to look into the issue and its relation with the increasing competition between the agricultural and commercial sector. Though it is not a new issue in land usage, the proposed model is considered as a new way to solve the problem. Though the results about land use efficiency are yet to be confirmed, the article still provides new insights to determine not only the solution to the problem, but also to be able to arrive in a good decision in the allocation of lands and spaces.
Foundations
The foundation of the article can be found in the previous studies of land optimization. In the past research studies, researchers used different methods for an effective land use plan, which became the theoretical foundations of the article. These methods include the Particle Swarm Optimization or PSO (Liu et al., 2012), the Soil and Water Assessment Tool or SWAT (Meyer, Lescot, & Laplana, 2009), the GIS habitat model (Meyer, Lescot, & Laplana, 2009), and AITSO (Zhao, Y. Liu, D. Liu, & Ma, 2015 ), and they are all significant contributions in land optimization. Also, the study area of these research studies were also in China, so external factors such as the topography and population will not make significant effects because they are relatively unchanged.
Analysis
In relation with the previous methods of land optimization, the genetic approach and application of the game theory can be a useful tool for solving the problem. Even if the results cannot be compared against the other methods, it is safe to say that the article made significant contributions in addressing the issue. Using the genetic approach, the generated patterns can be individually analyzed based on their possible efficiency when implemented. In addition to this, considering the competition surrounding the agricultural and commercial sector, the article, using the game theory, will help both sectors and the government to come up with a wise decision concerning the allocation of land use (Liu et al., 2015). Theoretically speaking, the article is able to address the issues of land optimization and fair competition simultaneously.
General Critique
Since there are other methods for land-use optimization, comparing the proposed model to them cannot be avoided. The similarity of genetic optimization with PSO, SWAT, GIS, and AISTO is that all of them consider the environmental and ecological benefits of the model. The difference, on the other hand, can be found on the mechanisms and the intended purpose of the methods: PSO based its method on the concept of zoning, where land areas are being defined by boundaries and limitations provided by law (Liu et al., 2012); SWAT and GIS habitat model aimed to maximized farming system as opposed to equal land-use distribution (Meyer, Lescot, & Laplana, 2009); and AISTO lacked in practicality due to its complex approach of the problem. Furthermore, the article discussed the underlying concepts of the proposed model, and is able to determine the significance of these concepts in finding a solution for the problem in land optimization. These concepts are new and the authors do not simply get the idea from past studies. The model is discussed in detail except that the information about the results is currently limited for the mean time (Liu et al., 2015). This is because the approach is relatively new and it is the first time testing the solution in a sample population and a certain location. Giving the experts more time to figure out its significance will be helpful in reflecting with the ideas and concepts used behind this article.
Issues
Land-use optimization is the main concern of the article. It is important especially this time because all establishments require land to be able to function. However, some portions of the lands are not used efficiently. As such, it is important to address this issue. Solving the issue will create more opportunity for more establishments or for the restoration of the environment.
Another issue tackled in the article is the increasing competition in land use. Nowadays, there is an increasing conflict between farmers and owners of establishment. They believed that one sector is being favored than the other one. Because of this, it is important to make a wise decision in allocating lands depending on the purpose. Addressing this issue will prevent worse confrontations and that both parties can come into an agreement.
Other Issues
Since government is involved in the negotiation, there is an issue of political agenda. It cannot be avoided because the government is subjective when it comes to these matters. Bias might become an issue especially if it concerns the interest of the government, It remained unsolved because there are no indications or proof that politics is involved with the government’s decision. In order to resolve the issue, the government must minimize their involvements on these matters and let the experts handle the negotiation.
Impact
The impact of the article has yet to be determined, because it is a relatively new approach and the authors are still in progress in determining the study’s significance. There might be little to no citation about the article, but once it has established its objectives, experts may be able to consider citing the article.
Questions
How strong is the relationship of land-use and competition considering the use of this model? What are the possible advantages of genetic optimization from the other methods stated in the outside references? Why genetic mechanisms must be incorporated with land-use optimization? In what way can genetic optimization be significant?
Annotated Bibliography
Meyer, B., Lescot, J., & Laplana, R. (2009). Comparison of two spatial optimization techniques: A framework to solve multiobjective land use distribution problems. Environmental Management, 43(2), 264-281.
The article discussed about the two techniques in spatial optimization, the SWAT and GIS. Both techniques aimed to maximize farming systems. The article is cited due to its different purpose. Since the agricultural sector is being aggravated by continuous development, this article can show the importance of agriculture.
Liu, Y., Wang, H., Ji, Y., Liu, Z., & Zhao, X. (2012). Land Use Zoning at the County Level Based on a Multi-Objective Particle Swarm Optimization Algorithm: A Case Study from Yicheng, China. International Journal of Environmental Research and Public Health, 9(8), 2801-2826.
The article considers zoning as a way to optimize land use. The article aimed to incorporate laws pertaining land use zoning to solve issues of efficiency. This article is cited because it is a different approach compared to the reviewed article. Furthermore, it is a case study, so data will surely be accurate and precise
Zhao, X., Liu, Y., Liu, D., & Ma, X. (2015). AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems. Computational Intelligence and Neuroscience.
This article shows the complexity of the AITSO. Even so, it is a different approach in solving land-use problems. The article is cited in order to show that land-use optimization is not an easy problem to deal with. It requires complex analysis and even today, the problem remained unsolved.
