def _business_one(self, agents, function, beta):
    'Performs the first business phase.\n\n        Args:\n            agents (list): List of agents.\n            function (Function): A Function object that will be used as the objective function.\n            beta (float): Range of fluctuation.\n\n        '
    agents.sort(key=(lambda x: x.fit))
    (A_1, A_2, A_3) = (copy.deepcopy(agents[0]), copy.deepcopy(agents[1]), copy.deepcopy(agents[2]))
    (q_1, q_2, _) = self._calculate_queue(len(agents), A_1.fit, A_2.fit, A_3.fit)
    case = None
    for (i, agent) in enumerate(agents):
        a = copy.deepcopy(agent)
        if (i < q_1):
            if (i == 0):
                case = 1
            A = copy.deepcopy(A_1)
        elif (q_1 <= i < (q_1 + q_2)):
            if (i == q_1):
                case = 1
            A = copy.deepcopy(A_2)
        else:
            if (i == (q_1 + q_2)):
                case = 1
            A = copy.deepcopy(A_3)
        alpha = r.generate_uniform_random_number((- 1), 1)
        E = r.generate_gamma_random_number(1, 0.5, (agent.n_variables, agent.n_dimensions))
        if (case == 1):
            e = r.generate_gamma_random_number(1, 0.5, 1)
            F_1 = (((beta * alpha) * (E * np.fabs((A.position - a.position)))) + (e * (A.position - a.position)))
            a.position = (A.position + F_1)
            a.fit = function(a.position)
            if (a.fit < agent.fit):
                agent.position = copy.deepcopy(a.position)
                agent.fit = copy.deepcopy(a.fit)
                case = 1
            else:
                case = 2
        else:
            F_2 = ((beta * alpha) * (E * np.fabs((A.position - a.position))))
            a.position += F_2
            a.fit = function(a.position)
            if (a.fit < agent.fit):
                agent.position = copy.deepcopy(a.position)
                agent.fit = copy.deepcopy(a.fit)
                case = 2
            else:
                case = 1
Performs the first business phase.

Args:
    agents (list): List of agents.
    function (Function): A Function object that will be used as the objective function.
    beta (float): Range of fluctuation.
def _business_one(self, agents, function, beta):
    'Performs the first business phase.\n\n        Args:\n            agents (list): List of agents.\n            function (Function): A Function object that will be used as the objective function.\n            beta (float): Range of fluctuation.\n\n        '
    agents.sort(key=(lambda x: x.fit))
    (A_1, A_2, A_3) = (copy.deepcopy(agents[0]), copy.deepcopy(agents[1]), copy.deepcopy(agents[2]))
    (q_1, q_2, _) = self._calculate_queue(len(agents), A_1.fit, A_2.fit, A_3.fit)
    case = None
    for (i, agent) in enumerate(agents):
        a = copy.deepcopy(agent)
        if (i < q_1):
            if (i == 0):
                case = 1
            A = copy.deepcopy(A_1)
        elif (q_1 <= i < (q_1 + q_2)):
            if (i == q_1):
                case = 1
            A = copy.deepcopy(A_2)
        else:
            if (i == (q_1 + q_2)):
                case = 1
            A = copy.deepcopy(A_3)
        alpha = r.generate_uniform_random_number((- 1), 1)
        E = r.generate_gamma_random_number(1, 0.5, (agent.n_variables, agent.n_dimensions))
        if (case == 1):
            e = r.generate_gamma_random_number(1, 0.5, 1)
            F_1 = (((beta * alpha) * (E * np.fabs((A.position - a.position)))) + (e * (A.position - a.position)))
            a.position = (A.position + F_1)
            a.fit = function(a.position)
            if (a.fit < agent.fit):
                agent.position = copy.deepcopy(a.position)
                agent.fit = copy.deepcopy(a.fit)
                case = 1
            else:
                case = 2
        else:
            F_2 = ((beta * alpha) * (E * np.fabs((A.position - a.position))))
            a.position += F_2
            a.fit = function(a.position)
            if (a.fit < agent.fit):
                agent.position = copy.deepcopy(a.position)
                agent.fit = copy.deepcopy(a.fit)
                case = 2
            else:
                case = 1