MATLAB之數學建模：深圳市生活垃圾處理社會總成本分析

時間  2019-11-24
標籤 matlab 之數 建模 深圳市 生活 垃圾處理 社會 總成本 分析 欄目 MATLAB 简体版
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MATLAB之數學建模：深圳市生活垃圾處理社會總成本分析

注：MATLAB版本--2016a,做圖分析部分見《MATLAB之折線圖、柱狀圖、餅圖以及經常使用繪圖技巧》html

一.現狀模式下的模型

%第一題：創建總成本分析模型/年：按現狀分析
% 總成本=直接成本 +經濟技術成本 + 社會成本
function dataPro = Total_Cost_Analysis(year)
%垃圾每一年預測表：2017-2030
table = [ 6.4450e+06   6.8317e+06 7.2416e+06   7.6761e+06   7.9832e+06   8.3025e+06   8.6346e+06 8.9800e+06   9.3392e+06   9.6193e+06   9.9079e+06  1.0205e+07   1.0511e+07   1.0827e+07];  %垃圾總量每一年數值（2017-2030）
rubbish_quantity = table(year-2016);
%將時間分期處理：2017-2020，2021-2025，2026-2030
switch year
    case { 2017,2018,2019,2020}          %近期
        rubbish_num_burn=215*10^4;            
        rubbish_num_landfill = rubbish_quantity-rubbish_num_burn;
        class_cost = 0;           
        handle_cost =  rubbish_num_landfill*60+ rubbish_num_burn*100;
        transport_cost = 0.5*rubbish_num_landfill*60+0.5*rubbish_num_landfill*70+...
                                    0.5*rubbish_num_burn*60+0.5*rubbish_num_burn*70 ;  
        social_cost =132*rubbish_quantity;                    
        technology_cost=1300*10^4;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
        subsidy = 100*rubbish_quantity;        %前期 100，中期50，後期取消，成本計算取負
        profit =  (10^(-4))*rubbish_quantity/102.49*10^8 ;
    case {2021,2022,2023,2024,2025}          %中期
         rubbish_num_burn =215*10^4;            
         rubbish_num_landfill = rubbish_quantity-rubbish_num_burn;
         class_cost = 0;         
         handle_cost =  rubbish_num_landfill*60+ rubbish_num_burn*150;
         transport_cost = rubbish_quantity*100;  
         social_cost =2*132*rubbish_quantity;                 
         technology_cost=1300*10^4;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy = 50*rubbish_quantity;         %前期 100，中期50，後期取消，成本計算取負
         profit =  (10^(-4))*rubbish_quantity*(1/104.15+1/100.1+1/317.46)*10^8 +rubbish_quantity/1.54*10^4;       %不一樣時間 定值
        
    case  {2026,2027,2028,2029,2030}        %遠期
         rubbish_num_burn =215*10^4;        
         rubbish_num_landfill = rubbish_quantity-rubbish_num_burn;
         class_cost = 0;           
         handle_cost =  rubbish_num_landfill*60+ rubbish_num_burn*180;
         transport_cost = rubbish_quantity*100;  
         social_cost =2*132*rubbish_quantity;                  
         technology_cost=1300*10^4;                      % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy = 0*rubbish_quantity;                     %前期 100，中期50，後期取消，成本計算取負
         profit =  (10^(-4))*rubbish_quantity*(1/104.15+1/50.05+1/222.22)*10^8 +rubbish_quantity/1.54*10^4 ;        %不一樣時間 定值                      
    otherwise
         msgbox('親，請從新輸入年份：');       
end

%設施投資: 
equipment_cost = 1.56*10^8;   

%輸出，分析:dataPro爲數據集合
profit =profit *0.15;    
direct_cost =  class_cost + transport_cost + equipment_cost + handle_cost;
total_cost = direct_cost+technology_cost +social_cost+subsidy-profit  ;
%dataPro（11）: 分類，收運，設施，處理，技術，社會，補貼，收益，直接，總，均
dataPro = [ class_cost,transport_cost,equipment_cost,handle_cost, ...
                     technology_cost,social_cost,subsidy,profit,direct_cost,total_cost,total_cost/rubbish_quantity];
       
end

二. 模式一

%模式一：總成本=直接成本 +經濟技術成本 + 社會成本
function dataPro = Total_Cost_Analysis_model1(year)
%垃圾每一年預測表：2017-2030
table = [ 6.4450e+06   6.8317e+06 7.2416e+06   7.6761e+06   7.9832e+06   8.3025e+06   8.6346e+06 8.9800e+06   9.3392e+06   9.6193e+06   9.9079e+06  1.0205e+07   1.0511e+07   1.0827e+07];  %垃圾總量每一年數值（2017-2030）
rubbish_quantity = table(year-2016);
%將時間分期處理：2014-2020，2021-2025，2026-2030
switch year
    case {2016,2017,2018,2019,2020}
        rubbish_num_burn=215*10^4;             %近期
        rubbish_num_landfill = rubbish_quantity-rubbish_num_burn;
        transport_cost = 0.5*rubbish_quantity*60+0.5*rubbish_quantity*70; 
        handle_cost =  rubbish_num_landfill*60+rubbish_num_burn*100; 
        social_cost = 132*rubbish_quantity;                 
        technology_cost=1300*10^4;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
        subsidy = 100*rubbish_quantity;       %前期 100，中期50，後期取消，成本計算取負
        profit = (10^(-4))*rubbish_quantity/102.49*10^8 ;            %不一樣時間 定值
         
    case {2021,2022,2023,2024,2025}
         transport_cost = rubbish_quantity*100;  
         handle_cost =  rubbish_quantity*150; 
         social_cost =8*132*rubbish_quantity;                    
         technology_cost=1300*10^4;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy = 50*rubbish_quantity;       %前期 100，中期50，後期取消，成本計算取負
         profit = (10^(-4))* rubbish_quantity*(1/52.1+1/100.1 )*10^8 +rubbish_quantity/0.77*10^4;                           
         
    case  {2026,2027,2028,2029,2030}
         transport_cost = rubbish_quantity*100;
         handle_cost =  rubbish_quantity*180; 
         social_cost =8*132*rubbish_quantity;                 
         technology_cost=1300*10^4;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy =  0*rubbish_quantity;       %前期 100，中期50，後期取消，成本計算取負
         profit =  (10^(-4))*rubbish_quantity*(1/52.07+1/50.05 )*10^8 +rubbish_quantity/0.77*10^4;           
         
    otherwise
         msgbox('親，請從新輸入年份：');       
end

%分類費用
class_cost = 0;     
%設施投資: 
equipment_cost =  0 ;  

%輸出，分析
profit =profit *0.15;    
 direct_cost =  class_cost + transport_cost + equipment_cost + handle_cost;
total_cost = direct_cost+technology_cost +social_cost+subsidy-profit  ;
%dataPro（11）: 分類，收運，設施，處理，技術，社會，補貼，收益，直接，總，均
dataPro = [ class_cost,transport_cost,equipment_cost,handle_cost, ...
                     technology_cost,social_cost,subsidy,profit,direct_cost,total_cost,total_cost/rubbish_quantity];

end

三. 模式二

%模式二：源頭分類收集+溼垃圾生物處理+幹垃圾焚燒+中心城區幹垃圾轉運 
function dataPro = Total_Cost_Analysis_model2(year)
%垃圾每一年預測表：2017-2030
table = [ 6.4450e+06   6.8317e+06 7.2416e+06   7.6761e+06   7.9832e+06   8.3025e+06   8.6346e+06 8.9800e+06   9.3392e+06   9.6193e+06   9.9079e+06  1.0205e+07   1.0511e+07   1.0827e+07];  %垃圾總量每一年數值（2017-2030）
rubbish_quantity = table(year-2016);
switch year
    case {2016,2017,2018,2019,2020}
        rubbish_num_burn=215*10^4;             %近期
        rubbish_num_landfill = rubbish_quantity-rubbish_num_burn;
        class_cost = 0;    
        transport_cost = 0.5*rubbish_quantity*60+0.5*rubbish_quantity*70;  
        handle_cost =  rubbish_num_landfill*60+rubbish_num_burn*100;   
        social_cost =132*rubbish_quantity;             
        technology_cost=1300*10^4+10^8;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
        subsidy = 100*rubbish_quantity;       %前期 100，中期50，後期取消，成本計算取負
        profit =  (10^(-4))*rubbish_quantity/102.49*10^8 ;                           %不一樣時間 定值
         
    case {2021,2022,2023,2024,2025}
         class_cost = 10.6*10^8;    
         transport_cost = 0.4*rubbish_quantity*60+0.6*rubbish_quantity*100;  
         handle_cost =   rubbish_quantity*150;
         social_cost =1.2*132*rubbish_quantity;                   % (year-2017)
         technology_cost=1300*10^4+0.7*10^8;           % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy = 50*rubbish_quantity;                          %前期 100，中期50，後期取消，成本計算取負
         profit =  (10^(-4))*rubbish_quantity*(1/72.31+1/396.83+1/100.1)*10^8 +rubbish_quantity/1.28*10^4 ;         %不一樣時間 定值
 
    case  {2026,2027,2028,2029,2030}
         class_cost = 10.6*10^8;    
         transport_cost = 0.5*rubbish_quantity*60+0.5*rubbish_quantity*100;   
         handle_cost =   0.5*rubbish_quantity*180+ 0.5*rubbish_quantity*200;
         social_cost =1.2*132*rubbish_quantity;                   % (year-2017)
         technology_cost=1300*10^4+0.4*10^8;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy =  0*rubbish_quantity;       %前期 100，中期50，後期取消，成本計算取負
         profit = (10^(-4))* rubbish_quantity*(1/77.98+1/277.78+1/50.05)*10^8 +rubbish_quantity/1.28*10^4;                        
         
    otherwise
         msgbox('親，請從新輸入年份：');       
end       

%設施投資: 
equipment_cost = 0;   

%輸出，分析
profit =profit *0.15;    
 direct_cost =  class_cost + transport_cost + equipment_cost + handle_cost;
total_cost = direct_cost+technology_cost +social_cost+subsidy-profit  ;
%dataPro（11）: 分類，收運，設施，處理，技術，社會，補貼，收益，直接，總，均
dataPro = [ class_cost,transport_cost,equipment_cost,handle_cost, ...
                     technology_cost,social_cost,subsidy,profit,direct_cost,total_cost,total_cost/rubbish_quantity];

end

四. 模式三

%模式三：混合收集+末端分類+溼垃圾生物處理+幹垃圾焚燒+中心城區幹垃圾轉運
function dataPro = Total_Cost_Analysis_model3(year)
%垃圾每一年預測表：2017-2030
table = [ 6.4450e+06   6.8317e+06 7.2416e+06   7.6761e+06   7.9832e+06   8.3025e+06   8.6346e+06 8.9800e+06   9.3392e+06   9.6193e+06   9.9079e+06  1.0205e+07   1.0511e+07   1.0827e+07];  %垃圾總量每一年數值（2017-2030）
rubbish_quantity = table(year-2016);
switch year
    case {2016,2017,2018,2019,2020}
        rubbish_num_burn=215*10^4;             %近期
        rubbish_num_landfill = rubbish_quantity-rubbish_num_burn;
        transport_cost = 0.5*rubbish_quantity *60+0.5*rubbish_quantity *70  ;  
        handle_cost =  rubbish_num_landfill*60+rubbish_num_burn*100; 
        social_cost =132*rubbish_quantity;                  
        technology_cost=1300*10^4+10^8;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
        subsidy = 100*rubbish_quantity;                  %前期 100，中期50，後期取消，成本計算取負
        profit =  (10^(-4))*rubbish_quantity/102.49*10^8 ;           %不一樣時間 定值
         
    case {2021,2022,2023,2024,2025}
         handle_cost =   0.5*rubbish_quantity*150+ 0.5*rubbish_quantity*200;
         transport_cost = 0.4*rubbish_quantity*60+0.6*rubbish_quantity*100;  
         social_cost =132*rubbish_quantity;                  
         technology_cost=1300*10^4+0.7*10^8;           % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy = 50*rubbish_quantity;                          %前期 100，中期50，後期取消，成本計算取負
         profit =  (10^(-4))*rubbish_quantity*(1/86.87+1/317.46+1/100.1)*10^8 +rubbish_quantity/1.54*10^4;          %不一樣時間 定值
                               
    case  {2026,2027,2028,2029,2030}
         handle_cost =   0.5*rubbish_quantity*180+ 0.5*rubbish_quantity*200;
         transport_cost = 0.4*rubbish_quantity*60+0.6*rubbish_quantity*100;  
         social_cost =132*rubbish_quantity;                    
         technology_cost=1300*10^4+0.4*10^8;            % 溼處理分期：10^8,0.7*10^8，0.4*10^8
         subsidy =  0*rubbish_quantity;               %前期 100，中期50，後期取消，成本計算取負
         profit =  (10^(-4))*rubbish_quantity*(1/86.80+1/222.22+1/50.05)*10^8 +rubbish_quantity/1.54*10^4;           %不一樣時間 定值
    
    otherwise
         msgbox('親，請從新輸入年份：');       
end  

%設施投資: 
equipment_cost = 0;   
%分類
class_cost = 0;   
%輸出，分析
profit =profit *0.15;    
direct_cost =  class_cost + transport_cost + equipment_cost + handle_cost;
total_cost = direct_cost+technology_cost +social_cost+subsidy-profit  ;
%dataPro（11）: 分類，收運，設施，處理，技術，社會，補貼，收益，直接，總，均
dataPro = [ class_cost,transport_cost,equipment_cost,handle_cost, ...
                     technology_cost,social_cost,subsidy,profit,direct_cost,total_cost,total_cost/rubbish_quantity];

 end

五. 垃圾總量預測

%垃圾總量預測
rubbish_table = zeros(1,14);
rubbish_table(1,1) = 541.14*10^4;    %2014年垃圾產量541.14萬噸
for year = 2015:2020
    rubbish_table(1,year-2013) =  rubbish_table (1,year-2014)*(1+0.06);
end
for year = 2021:2025
    rubbish_table(1,year-2013) =  rubbish_table (1,year-2014)*(1+0.04);
end
for year = 2026:2030
    rubbish_table(1,year-2013) =  rubbish_table (1,year-2014)*(1+0.03);
end

六.各模式數據彙總

% 總成本=直接成本 +經濟技術成本 + 社會成本
%數據收集data_model（從2017-2030年：現狀，模式一，模式二，模式三）
clear;close;clc;
data_model0 = zeros(14, 11);
data_model1 = zeros(14, 11);
data_model2 = zeros(14, 11);
data_model3 = zeros(14, 11);
for year = 2017 : 2030
    dataPro0 = Total_Cost_Analysis(year );                %現狀
    dataPro1 = Total_Cost_Analysis_model1(year );
    dataPro2 = Total_Cost_Analysis_model2(year );
    dataPro3 = Total_Cost_Analysis_model3(year );
    for i = 1:11
        data_model0(year-2016,i) = dataPro0(i);
        data_model1(year-2016,i) = dataPro1(i);
        data_model2(year-2016,i) = dataPro2(i);
        data_model3(year-2016,i) = dataPro3(i);
    end
end

七.最優模式評選

%優選模式計算：分類0.3，設施0.5，收運1.5，處理1，技術1，社會1.7，收益-2
%原理較複雜，優選模式以遠期成本最優，而且設定不一樣成本的比重，所得結果爲每噸垃圾的成本
%
table = [9.6193e+06   9.9079e+06  1.0205e+07   1.0511e+07   1.0827e+07];  %垃圾總量每一年數值（遠期2025-2030）
rubbish_quantity = sum(table,2);

x=0.3*sum(data_model0(10:14,1))+0.5*sum(data_model0(10:14,3))+1.5*sum(data_model0(10:14,2))+...
      1*sum(data_model0(10:14,4))+1*sum(data_model0(10:14,5))+1.7*sum(data_model0(10:14,6))+...
        2*sum(data_model0(10:14,8));
table0 =x/rubbish_quantity     %現狀模式 /rubbish_quantity 

x=0.3*sum(data_model1(10:14,1))+0.5*sum(data_model1(10:14,3))+1.5*sum(data_model1(10:14,2))+...
      1*sum(data_model1(10:14,4))+1*sum(data_model1(10:14,5))+1.7*sum(data_model1(10:14,6))+...
        2*sum(data_model1(10:14,8));
table1 =  x/rubbish_quantity     %模式一

x=0.3*sum(data_model2(10:14,1))+0.5*sum(data_model2(10:14,3))+1.5*sum(data_model2(10:14,2))+...
      1*sum(data_model2(10:14,4))+1*sum(data_model2(10:14,5))+1.7*sum(data_model2(10:14,6))+...
        2*sum(data_model2(10:14,8));
table2 =  x/rubbish_quantity     %模式二

x=0.3*sum(data_model3(10:14,1))+0.5*sum(data_model3(10:14,3))+1.5*sum(data_model3(10:14,2))+...
      1*sum(data_model3(10:14,4))+1*sum(data_model3(10:14,5))+1.7*sum(data_model3(10:14,6))+...
        2*sum(data_model3(10:14,8));
table3 =  x/rubbish_quantity    %模式三
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