• 模拟退火算法解决快递公司送货策略问题


    clear	
    	clc
        x=xlsread('送货.xlsx','C3:C32');
        y=xlsread('送货.xlsx','D3:D32');
        num=xlsread('送货.xlsx','A3:A32');
    	a = 0.99;	% 温度衰减函数的参数
    	t0 = 97; tf = 3; t = t0;
    	Markov_length = 10000;	% Markov链长度
    	coordinates = [num,x,y];
    	coordinates(:,1) = [];
    	amount = size(coordinates,1); 	% 城市的数目
    	% 通过向量化的方法计算距离矩阵
    	dist_matrix = zeros(amount, amount);
    	coor_x_tmp1 = coordinates(:,1) * ones(1,amount);
    	coor_x_tmp2 = coor_x_tmp1';
    	coor_y_tmp1 = coordinates(:,2) * ones(1,amount);
    	coor_y_tmp2 = coor_y_tmp1';
    	dist_matrix = abs(coor_x_tmp1-coor_x_tmp2)+ ...
    					abs(coor_y_tmp1-coor_y_tmp2);
    
    	sol_new = 1:amount;         % 产生初始解
    % sol_new是每次产生的新解;sol_current是当前解;sol_best是冷却中的最好解;
    	E_current = inf;E_best = inf; 		% E_current是当前解对应的回路距离;
    % E_new是新解的回路距离;
    % E_best是最优解的
    	sol_current = sol_new; sol_best = sol_new;          
    	p = 1;
    
    	while t>=tf
    		for r=1:Markov_length		% Markov链长度
    			% 产生随机扰动
    			if (rand < 0.5)	% 随机决定是进行两交换还是三交换
    				% 两交换
    				ind1 = 0; ind2 = 0;
    				while (ind1 == ind2)
    					ind1 = ceil(rand.*amount);
    					ind2 = ceil(rand.*amount);
    				end
    				tmp1 = sol_new(ind1);
    				sol_new(ind1) = sol_new(ind2);
    				sol_new(ind2) = tmp1;
    			else
    				% 三交换
    				ind1 = 0; ind2 = 0; ind3 = 0;
    				while (ind1 == ind2) || (ind1 == ind3) ...
    					|| (ind2 == ind3) || (abs(ind1-ind2) == 1)
    					ind1 = ceil(rand.*amount);
    					ind2 = ceil(rand.*amount);
    					ind3 = ceil(rand.*amount);
    				end
    				tmp1 = ind1;tmp2 = ind2;tmp3 = ind3;
    				% 确保ind1 < ind2 < ind3
    				if (ind1 < ind2) && (ind2 < ind3)
    					;
    				elseif (ind1 < ind3) && (ind3 < ind2)
    					ind2 = tmp3;ind3 = tmp2;
    				elseif (ind2 < ind1) && (ind1 < ind3)
    					ind1 = tmp2;ind2 = tmp1;
    				elseif (ind2 < ind3) && (ind3 < ind1) 
    					ind1 = tmp2;ind2 = tmp3; ind3 = tmp1;
    				elseif (ind3 < ind1) && (ind1 < ind2)
    					ind1 = tmp3;ind2 = tmp1; ind3 = tmp2;
    				elseif (ind3 < ind2) && (ind2 < ind1)
    					ind1 = tmp3;ind2 = tmp2; ind3 = tmp1;
    				end
    				
    				tmplist1 = sol_new((ind1+1):(ind2-1));
    				sol_new((ind1+1):(ind1+ind3-ind2+1)) = ...
    					sol_new((ind2):(ind3));
    				sol_new((ind1+ind3-ind2+2):ind3) = ...
    					tmplist1;
    			end
    
    			%检查是否满足约束
    			
    			% 计算目标函数值(即内能)
    			E_new = 0;
    			for i = 1 : (amount-1)
    				E_new = E_new + ...
    					dist_matrix(sol_new(i),sol_new(i+1));
    			end
    			% 再算上从最后一个城市到第一个城市的距离
    			E_new = E_new + ...
    				dist_matrix(sol_new(amount),sol_new(1));
    			
    			if E_new < E_current
    				E_current = E_new;
    				sol_current = sol_new;
    				if E_new < E_best
    % 把冷却过程中最好的解保存下来
    					E_best = E_new;
    					sol_best = sol_new;
    				end
    			else
    				% 若新解的目标函数值小于当前解的,
    				% 则仅以一定概率接受新解
    				if rand < exp(-(E_new-E_current)./t)
    					E_current = E_new;
    					sol_current = sol_new;
    				else	
    					sol_new = sol_current;
    				end
    			end
    		end
    		t=t.*a;		% 控制参数t(温度)减少为原来的a倍
    	end
    
    	disp('最优解为:')
    	disp(sol_best)
    	disp('最短距离:')
    	disp(E_best)
    

      

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  • 原文地址:https://www.cnblogs.com/tavee/p/13356883.html
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