optimization - 使用 ORtools 求解器进行图形着色的目标函数

Question

我写了一个 cp 函数来用 ORtools 解决图形着色

（最小化颜色使用，当边缘上每两个顶点的颜色需要不同时）我得到奇怪的结果，这不是最优的，我不知道为什么 - 我认为我的目标函数是错误的，或者我的约束公式是错误的，任何帮助? 谢谢

    def cp_with_ortools(node_count, edge_count, edges, M, solution, max_degree):
        global colors
        from ortools.sat.python import cp_model
        solution = [0] * (node_count)# list of colors to nodes initialized with 0
        # Creates the model.
        model = cp_model.CpModel()

        # Creates the variables.
        for i in range(node_count):
            solution[i] = model.NewIntVar(0, int(node_count), '')
            #shouldnt be max_degree? isnt working..
            
        # Adds  constraint
        for edge in edges:
            model.Add(solution[edge[0]] != solution[edge[1]])

        # Create the objective function
        obj_var = model.NewIntVar(0, node_count, 'makespan')
        model.AddMaxEquality(obj_var,solution)
        model.Minimize(obj_var)

        #model.Minimize(len(set(solution)))
        #model.Minimize(sum(solution)))

        # Creates a solver and solves the model.
        solver = cp_model.CpSolver()

        status = solver.Solve(model)

        if status == cp_model.OPTIMAL:
            colors = [solver.Value(solution[i]) for i in range(node_count)]

        return colors

标签： optimizationor-toolsconstraint-programminggraph-coloringobjective-function