2020 American Collegiate Mathematical Contest in Modeling
Question F The place I call home
Reproduction of the original title:
Several island nations, including the Maldives, Tuvalu, Kiribati and the Marshall Islands, are in danger of disappearing entirely due to rising sea levels, researchers have found. When an island nation's land disappears, what happens, or should happen, to the island's population? These environmentally displaced persons not only need to be resettled, but may also lose their unique culture, language and way of life. In this regard, we ask you to look more closely at the issue in terms of both relocating populations and preserving culture. There are many considerations and questions to be addressed, including: Where will these environmentally displaced people go? Which countries will accept them? Given that countries have historically and currently contributed disproportionately to greenhouse gases, accelerating climate change associated with rising sea levels, should the worst offenders have a higher obligation to address them? Also, who has the power to decide where these stateless environmentally displaced people establish new homes—individuals, intergovernmental organizations like the United Nations, or the individual governments of the countries that absorb them? You will need to address these issues in more detail in your essay starting on page 3.
Due to a recent UN ruling that theoretically recognizes environmentally displaced persons as refugees, the International Climate Migration Foundation (ICM-F) has hired you to advise the UN on developing a model and using it to analyze this multifaceted problem, Such as when, why, and how the United Nations should play a role in addressing growing energy policy challenges. The ICM-F plans to brief the United Nations on guidance on how the United Nations should formulate a systemic response to environmental displacement, particularly taking into account the desire to preserve cultural heritage. Your task is to develop a model (or set of models) and use your model to provide analysis in support of this policy. ICM-F is particularly interested in understanding the scope of the issue of environmentally displaced persons. For example, how many people are currently at risk of being environmentally displaced[1]; what are the values of risk country culture; and how might these answers change over time? Also, how should the world respond to an international policy that specifically focuses on protecting the rights of people whose countries are disappearing in the face of climate change, while also focusing on preserving culture? Based on your analysis, what advice can you make on the matter, and what would it mean to accept or reject your advice?
This question is very complex. I understand that your submission does not adequately consider all of the aspects described in the question paper beginning on page 3. However, taking into account the various aspects you have covered, synthesize your work into a cohesive answer to the ICM-F, as they suggest to the UN. Your team's paper should include at least:
Analysis of the scope of the problem in terms of both the number of people at risk and the risk of losing their culture;
proposed policy that addresses environmental displacement from a human rights perspective (able to resettle and participate fully in life in their new home) and cultural preservation;
description of the measures used to measure the proposed policy Model development of potential impact;
explanation of how the model is used to design and/or improve the proposed strategy;
supported by your analysis, an explanation of the importance of implementing your proposed strategy
Overview of the overall solution process (abstract)
A recent UN ruling has brought environmental refugees into sharp focus. Among them, the resettlement of climate refugees caused by climate change has also entered the public eye. In order to better understand and effectively deal with this problem, we decompose the problem to be solved and build corresponding models in turn.
When clarifying the research object, we simplified the definition of climate refugees in the model, and only predicted the number of climate refugees caused by sea level rise. Subsequent models are based on this premise.
First, we constructed a regression function based on the topography and population distribution of six selected countries, combined with current sea level change data and linear regression. Through the application of this model, it is estimated that by 2080, there will be approximately 200,000 to 300,000 climate refugees. Secondly, 300 factors affecting cultural loss were selected, and the influencing mechanisms of different factors were clarified through principal component analysis, which provided a direction for supranational organizations to formulate policies to reduce the risk of cultural loss in the country of origin.
Then, to find the optimal destinations of refugee flows, we extend the full bipartite graph by an analogical analysis hierarchical process (AHP). Use easy-to-detect indicators to determine the four general factors of target country acceptance, climate refugees, natural factors, and target country environmental responsibility, that is, to establish an adaptability evaluation system. Regarding the optimal flow direction, we use the KM algorithm to achieve the optimal match between climate refugees and receiving countries based on a complete bipartite graph of matching degrees.
Third, we consider the dynamics of protecting the human rights of climate refugees and their implications for cultural exchange and dissemination. We use five factors: per capita education level, per capita medical level, per capita food production, per capita pension expenditure, and per capita housing area to reflect the human rights protection status of climate refugees. We use PCA to combine these indicators into a new indicator, namely human rights protection degree indicator. In the early stage of climate refugee migration, this paper explores the knock-on effect of the number of climate refugees on the human rights protection capacity of refugee-hosting countries. Undoubtedly, the influx of population has diluted the per capita share of resources and reduced the human rights protection capacity of refugee-receiving countries. But in the long run, the potential contribution of climate refugees in the future will have an impact on the ability to protect human rights, and its operating mechanism is crucial to solving the problem. Due to the nature of culture, propagation and dissemination often takes time to support it. We hypothesize that, in the early stages of climate refugee migration, the host countries of climate refugees themselves have a different type of balanced culture. Due to the migration of climate refugees, the exchange and dissemination of the two cultures will have an impact. Here, we define cultures as three types: earning, losing, and swinging. Different culture types have different gains or losses due to spreading and spreading. We quantify gains or losses from exchange and diffusion across the three cultures and model how they balance out. A System Dynamics Model (SDM) clearly shows the dynamics of the system. Any parameter change will have a different impact on the outcome, whether it is the protection of human rights or the balance of cultural gains and losses.
Fourth, based on the above-mentioned system dynamics model, clarify the mechanism by which policy-related parameters affect the model. We set the goals for the proposed policy and extend the policy forward. The implementation of these policies to protect the human rights and culture of climate refugees will change some parameters, and the model results indicate the potential impact of these policies. At the same time, in order to further optimize the model, we added new parameters according to the analysis results to improve the accuracy of the model.
Finally, based on the results of all the above models, we shed light on the importance of implementing the proposed policy.
Model assumptions:
As mentioned above, we made several assumptions in our model.
When a country's sea level falls below 5 meters, its inhabitants are considered climate refugees and need to be resettled.
Assuming that the selected countries are representative, the identified impact mechanisms of cultural loss can be applied to other countries.
Migration of climate refugees must be done in groups, that is, the population of the country of origin is fully relocated to the same receiving country. However, the receiving country can accommodate multiple groups.
Refugees do not choose which country they settle in, UNHCR and other organizing groups tell them this.
Refugee-receiving countries must accept refugees assigned by international organizations, but their capacity is limited, and once capacity is reached, they can be rejected.
There have been no unexpected terrorist incidents or disasters in host countries following the migration of climate refugees.
Once climate refugees move in, they will have the same legal status as the original residents of the host country.
There is no isolation between nations, and the exchange and dissemination of the two cultures will definitely take place.
The policies of international organizations are mandatory, and the corresponding refugee-receiving countries must perfectly implement the policy recommendations put forward by international organizations.
Question restatement:
The International Climate Migration Foundation (ICM-F) hired us to develop a model to advise the UN on the resettlement of climate refugees and the protection of their cultural heritage, simulating the potential impact and importance of this policy. First, we must give a clear definition of climate refugees for modeling studies.
The recent UN ruling that governments cannot send people back to countries where their lives could be threatened by climate change is a potential game-changer — not just for climate refugees, but for global climate action as well. Meanwhile, the ruling further elaborated: "Given that the risk of an entire nation being submerged under water is so extreme, the conditions of life in such a nation may be incompatible with the right to life with dignity and then with dignity before the risk is realized." The right to life is incompatible. Based on the above explanations and the requirements of the question, we narrowed down the scope of the climate refugees studied in the model and defined them as a collective effort to escape the threat due to the continuous erosion of their living space by the greenhouse effect. Sexual migration Refugees. Residents of coastal small island countries such as Tuvalu, Maldives and Kisbads will become climate refugees in the future.
In order to solve the problems of refugee resettlement and cultural heritage protection brought about by climate change, we have decided to take the following measures:
Task 1: By building a model, select <> countries at risk, and predict the number and development trend of climate refugees caused by sea level rise in the future. At the same time, our model should identify the mechanisms by which selected factors affect the risk of cultural heritage loss for climate refugees.
Task 2: Our model is used to determine the optimal flow of climate refugees. We established an indicator system composed of subtypes to measure the degree of fit, and based on the degree of fit, we constructed a bipartite graph model of climate refugees and host countries. The model was used to best match the two to determine the optimal flow of climate refugees.
Task 3: Use our model to assess the human rights protection capacity of climate refugee host countries and the impact of two cultural exchanges and dissemination to understand how migration will affect their human rights and the net gain of cultural exchange and dissemination. What will change between the two over time. If we define a corresponding return-loss balance point, the model should predict when this critical point can be reached.
Task 4: Develop corresponding policies based on the results of Task 3. Let our model show how state-driven interventions would affect changes in human rights protection capacity and net benefits to illustrate the potential impact of policy interventions.
Task 5: Identify dynamic effects that the model ignores and modify the model accordingly. Based on the results of the above model, the importance of policy implementation is explained.
Model establishment and solution Overall paper thumbnail
For all papers, please see below "Only modeling QQ business cards" Click on the QQ business card
Part of the program code: (code and documentation not free)
function result=imm_index(rawdata,weight)
year=11;%»ØËÝÄê·Ý
n_var=6;%±äÁ¿Êý
middata(year,n_var)=0;
zhishu=2;
for i=1:n_var
mean0=mean(rawdata(:,i));
max0=max(rawdata(:,i));
min0=min(rawdata(:,i));
for i2=1:year
mid0=rawdata(i2,i);
middata(i2,i)=((mid0-mean0)/(max0-min0))/2+1.5;
end
end
reefu=middata(:,1);
outdata(year,n_var)=0;
%Ö¸±ê¼ÆËã
for i2=1:year%ÐÐ
outdata(i2,1)=reefu(i2)^zhishu/middata(i2,2)/3.75*4-(1/3.75);%gdpÔö³¤
outdata(i2,2)=middata(i2,3)/reefu(i2)^zhishu*4/7-4/7;%ͨÕÍ
outdata(i2,3)=middata(i2,4)/reefu(i2)^zhishu*4/7-4/7;%ʧҵ
outdata(i2,4)=reefu(i2)^zhishu/middata(i2,5)/3.75*4-(1/3.75);%ÈË¿Ú
outdata(i2,5)=middata(i2,6)/reefu(i2)^zhishu*4/7-4/7;%·¸×ï
end
weight=[2 2 2 1 2];
result=zeros(year,1);
for i=1:year
for i2=1:n_var-1
result(i)=weight(i2)*outdata(i,i2)+result(i);
end
end
end