num) # r2重新生成 left, right = min(r1, r2), max(r1, r2) # left 为r1,r2小值 ,r2为大值 ind_a1 = ind_a.copy() # 父亲 ind_b1 = ind_b.copy() # 母亲 for i in range(left, right + 1): ind_a2 = ind_a.copy() ind_b2 = ind_b.copy() ind_a[i] = ind_b1[i] # ...
max_generation = 1000; % 迭代的最大代数 probmutation = 0.16; % 变异的概率 % 使用种子初始化随机数生成器。 rand('seed',103); % 初始化种群:从随机路线开始 pop = zeros(popSize,numberofcities); for i=1:popSize pop(i,:)=randperm(numberofcities); end for generation = 1:max_generation %...
num) left, right = min(r1, r2), max(r1, r2) ind_a1 = ind_a.copy() ind_b1 = ind_b.copy() for i in range(left, right + 1): ind_a2 = ind_a.copy() ind_b2 = ind_b.copy() ind_a[i] = ind_b1[i] ind_b[i] = ind_a1[i] x = np.argwhere(ind_a == ind_a[i]...
for(inti=0;i<1<<n;i++) 的顺序递增就可以了。因为每个集合的子集的二进制数都比它的二进制数小。 在计算机里面,计算的次序,赋值的次序极端重要!把一个数学式子抄到算法里面一定要注意计算的次序。不然就容易出现新值把旧值覆盖,或者用没有正确更新的上一个值去计算下一个值的情况。之前在图论问题里面用DP...
Strong gains in the stock-based TSP funds in 2023 pushed the average account for federal employees and retirees back to roughly the levels before the
Through our computational study, we found that existing TSP solvers exhibit good performance, allowing near-optimal solutions to be obtained in less than a second for real-world scale SPRP-SS instances. Moreover, the efficiency of these TSP solvers remains unaffected by the number of cross ...
numIter = max(1,round(real(numIter(1))); showProg = logical(showProg(1)); showResult = logical(showResult(1)); showWaitbar = logical(showWaitbar(1)); % Initialize the Population pop = zeros(popSize,n); pop(1,:) = (1:n); for...
"title": "Creates a completion for the provided prompt, parameters and chosen model.", "parameters": { "endpoint": "{endpoint}", "api-version": "2023-09-01-preview", "deploymentId": "<deployment-id>", "body": { "prompt": [ "tell me a joke about mango" ], "max_tokens": 32...
chb2=max(c1,c2); cros=Tour_pbest(i,chb1:chb2); %交叉区域矩阵 ncros=size(cros,2); %交叉区域元素个数 %删除与交叉区域相同元素 for j=1:ncros for k=1:n if xnew1(i,k)==cros(j) xnew1(i,k)=0; for t=1:n-k temp=xnew1(i,k+t-1); ...
for path in my_list: len_list.append(path_length(d_matrix,path,size)) max_len=max(len_list)+1e-10 gen_best_length=min(len_list) # 种群中最优路径的长度 gen_best_length_index=len_list.index(gen_best_length) # 最优个体在种群中的索引 ...