CPLEX-python (3.6) 不斷顯示“未列出”錯誤

Question

我正在使用帶有 python 3.6 的 CPLEX 求解器來求解數學規划模型。 我曾經在我的舊計算機上執行此操作，現在在新計算機上重新安裝 cplex 沒有問題，但是當我嘗試運行最初運行沒有錯誤的模型時，現在我總是遇到相同的錯誤，例如對於旅行推銷員問題：

TypeError                                 Traceback (most recent call last)
~\Dropbox\CPLEX\TSP_MTZ\TSP.py in <module>
    137
    138
--> 139 TSP(4)

~\Dropbox\CPLEX\TSP_MTZ\TSP.py in TSP(N)
     38                 for j in range(N):
     39                         x_varobj.append(float(c[i,j]))
---> 40         Model.variables.add(obj = x_varobj, lb = x_varlb, ub = x_varub, types = x_vartypes, names = x_varnames)
     41
     42         u_vars=list(np.array(["u("+str(i)+")" for i in range(0,N)]))

c:\users\healh\.conda\envs\py36\lib\site-packages\cplex\_internal\_subinterfaces.py in add(self, obj, lb, ub, types, names, columns)
    454                                                      columns)
    455         return self._add_iter(self.get_num, self._add,
--> 456                               obj, lb, ub, types, names, columns)
    457
    458     def delete(self, *args):

c:\users\healh\.conda\envs\py36\lib\site-packages\cplex\_internal\_baseinterface.py in _add_iter(getnumfun, addfun, *args, **kwargs)
     39         """non-public"""
     40         old = getnumfun()
---> 41         addfun(*args, **kwargs)
     42         return range(old, getnumfun())
     43

c:\users\healh\.conda\envs\py36\lib\site-packages\cplex\_internal\_subinterfaces.py in _add(self, obj, lb, ub, types, names, columns)
    376         if columns == []:
    377             CPX_PROC.newcols(self._env._e, self._cplex._lp, obj, lb, ub,
--> 378                              types, names)
    379         else:
    380             with CPX_PROC.chbmatrix(columns, self._cplex._env_lp_ptr,

c:\users\healh\.conda\envs\py36\lib\site-packages\cplex\_internal\_procedural.py in newcols(env, lp, obj, lb, ub, xctype, colname)
    965         status = CR.CPXXnewcols(
    966             env, lp, ccnt, c_obj, c_lb, c_ub,
--> 967             xctype, colname)
    968     check_status(env, status)
    969

c:\users\healh\.conda\envs\py36\lib\site-packages\cplex\_internal\_pycplex.py in CPXXnewcols(env, lp, ccnt, py_obj, py_lb, py_ub, xctype, colname)
   1783
   1784 def CPXXnewcols(env: 'CPXCENVptr', lp: 'CPXLPptr', ccnt: 'CPXDIM', py_obj: 'double const *', py_lb: 'double const *', py_ub: 'double const *', xctype: 'char const *', colname: 'char const *const *') -> "int":
-> 1785     return _pycplex_platform.CPXXnewcols(env, lp, ccnt, py_obj, py_lb, py_ub, xctype, colname)
   1786
   1787 def CPXXaddcols(env: 'CPXCENVptr', lp: 'CPXLPptr', ccnt: 'CPXDIM', nzcnt: 'CPXNNZ', py_obj: 'double const *', py_matbeg: 'CPXNNZ const *', py_lb: 'double const *', py_ub: 'double const *', colname: 'char const *const *') -> "int":

TypeError: not a list

我的代碼如下：

import time
import numpy as np
import cplex
from cplex import Cplex
from cplex.exceptions import CplexError
import sys
import networkx as nx
import matplotlib.pyplot as plt
from openpyxl import Workbook
import xlrd

def TSP(N):
    wb = Workbook()
    ws = wb.active
    book = xlrd.open_workbook('C.xlsx')            #LECTURA DE PARÁMETROS.
    sheet = book.sheet_by_name("C")
    c=[[int(sheet.cell_value(r,c)) for c in range(sheet.ncols)] for r in range(sheet.nrows)]
    c=np.matrix(c)  
    print("")
    print("MATRIZ DE DISTANCIAS")
    print("")        
    print(c)    
    print("")
    print("")
    print("") 

    Model=cplex.Cplex()

    x_vars=np.array([["x("+str(i)+","+str(j)+")" for j in range(N)] for i in range(N)])
    x_varnames = x_vars.flatten()
    x_vartypes='B'*N*N
    x_varlb = [0.0]*len(x_varnames)
    x_varub = [1.0]*len(x_varnames)
    x_varobj = []
    for i in range(N):
        for j in range(N):
            x_varobj.append(float(c[i,j]))
    Model.variables.add(obj = x_varobj, lb = x_varlb, ub = x_varub, types = x_vartypes, names = x_varnames)

    u_vars=np.array(["u("+str(i)+")" for i in range(0,N)])
    u_varnames=u_vars.flatten()
    u_vartypes='I'*N
    u_varlb=[1.0]*N
    u_varub=[float(N)-1.0]*N
    u_varobj=[0.0]*N

    Model.variables.add(obj = u_varobj, lb = u_varlb, ub = u_varub, types = u_vartypes, names = u_varnames)
    Model.objective.set_sense(Model.objective.sense.minimize)
    # suma(J,x[i,j])==1.0, forall i in N
    for i in range(N):
        row1=[]
        val1=[]
        for j in range(N):
            row1.append(x_vars[i,j])
            val1.append(1.0)

        Model.linear_constraints.add(lin_expr = [cplex.SparsePair(ind = row1, val= val1)], senses = 'E', rhs = [1.0])

    # suma(i,x[i,j])==1.0, forall j in N
    for j in range(N):
        row2=[]
        val2=[]
        for i in range(N):
            row2.append(x_vars[i,j])
            val2.append(1.0)

        Model.linear_constraints.add(lin_expr = [cplex.SparsePair(ind = row2, val= val2)], senses = 'E', rhs = [1.0])
    
    #u[i]-u[j]-(N-1)x[i,ji]<=N-2 , forall i in N, forall j in N, con i!=j.
    for i in range(1,N):
        for j in range(1,N):
            if i!=j:
                row3=[]
                val3=[]
                row3.append(u_vars[i])
                val3.append(1.0)
                row3.append(u_vars[j])
                val3.append(-1.0)
                row3.append(x_vars[i,j])
                val3.append(float(N)-1.0)
                Model.linear_constraints.add(lin_expr = [cplex.SparsePair(ind = row3, val= val3)], senses = 'L', rhs = [float(N)-2.0])

    
    solution=Model.solve()
    Model.write('modelo.lp')
    #Model.parameters.mip.pool.relgap.set(0.6)
    
    pool_solution=Model.populate_solution_pool()
    #print(pool_solution)

    def show_solution():
        print("\nVARLOS FUNCION OBJETIVO - DISTANCIA MINIMIA = {}".format(Model.solution.get_objective_value()))
        V=[i for i in range(N)]
        E=[]
        E1=[(i,j) for i in range(N) for j in range(N) if i!=j]
        for i in range(0,N):
            for j in range(0,N):
                if(Model.solution.get_values("x("+str(i)+","+str(j)+")")!=0.0):
                    print("x("+str(i)+","+str(j)+")"+" = "+str(Model.solution.get_values("x("+str(i)+","+str(j)+")")))
                    E.append((i,j))
        print("")

        for i in range(0,N):
            if(Model.solution.get_values("u("+str(i)+")")!=0.0):
                print("u("+str(i)+")"+" = "+str(Model.solution.get_values("u("+str(i)+")")))
        print("")

        G=nx.DiGraph()
        G.add_edges_from(E)
        G.add_nodes_from(V)

        
        pos=nx.spring_layout(G,k=0.3)

        print(Model.solution.get_values("x("+str(1)+","+str(0)+")")) #OBTENER VALOR DE UNA VARIABLE.
        print("ESTATUS_DE_LA_SOLUCION_ENCONTRADA:", Model.solution.get_status_string())
        print("SOLUCION_PRIMAL_OPTIMA?:", Model.solution.is_primal_feasible())
        #print(Model.variables.get_cols())
        
        nx.draw_networkx_nodes(G, pos)
        nx.draw_networkx_labels(G, pos)
        nx.draw_networkx_edges(G, pos, edgelist=E1, edge_color='blue', width=0.3 ,arrows=True) # highlight elist
        nx.draw_networkx_edges(G, pos, edge_color='black', width=1.8,arrows=True) # show all edges, thin lines
        

# turn off axis markings
        plt.axis('off')
        plt.savefig('grafo_tsp.png',dpi=20)
        plt.show()
    
    show_solution()

TSP(4)

這是數據：

我真的不明白這個問題，我以前每天都這樣做，現在我遇到了這個問題，有什么提示嗎？

Answer 1

問題是

x_varnames = x_vars.flatten()

將x_varnames創建為 numpy 數組，而variables.add()的names參數應為列表。

您可以通過將x_varnames定義為來解決此問題

x_varnames = x_vars.flatten().tolist()

我不確定是 CPLEX 中的更改還是 numpy 中的更改導致了此問題。