基于金豺优化算法python代码

import numpy as np# 定义适应度函数
def fitness_func(x):return sum(x2)# 初始化金豺群体
def init_jackal_population(num_jackals, dim):jackals = []for i in range(num_jackals):jackal = np.random.uniform(low=-5, high=5, size=dim)jackals.append(jackal)return jackals# 计算每个金豺的适应度值
def calc_fitness(jackals):fitness = []for jackal in jackals:fitness.append(fitness_func(jackal))return fitness# 选择领袖金豺
def select_leader_jackal(jackals, fitness):idx = np.argmin(fitness)return jackals[idx]# 更新金豺位置
def update_jackal_position(jackal, leader_jackal, a, r1, r2):new_jackal = jackal + a * (np.exp(-r1) - np.exp(-r2)) * np.abs(leader_jackal - jackal)return new_jackal# 运行金豺优化算法
def run_gjo(num_iterations, num_jackals, dim):# 初始化金豺群体jackals = init_jackal_population(num_jackals, dim)# 计算每个金豺的适应度值fitness = calc_fitness(jackals)# 选择领袖金豺l