我想在多核环境下运行scipy的differential_evolution函数，参数为workers。
我已经按照documentation的说明，开发了以下脚本来检查函数在使用和不使用workers参数时的运行时间：

import time

if __name__ == '__main__':
    from scipy.optimize import differential_evolution, rosen
    bounds = [( 0, 2 ), ( 0, 2 ), ( 0, 2 ), ( 0, 2 ), ( 0, 2 )]

    print( 'Beginning optimisation without parallelisation' )
    start = time.time()
    result = differential_evolution( rosen, bounds,
                                     workers=1,
                                     popsize=200,
                                     maxiter=1000,
                                     tol=0.001,
                                     seed=1 )
    end = time.time()
    print( 'Optimisation finished after {} seconds'.format( round( end - start, 2 ) ) )

    print( '\nBeginning optimisation with workers parameter set to 10' )
    start = time.time()
    result = differential_evolution( rosen, bounds,
                                     updating='deferred',
                                     workers=10,
                                     popsize=200,
                                     maxiter=1000,
                                     tol=0.001,
                                     seed=1 )
    end = time.time()
    print( 'Optimisation finished after {} seconds'.format( round( end - start, 2 ) ) )

运行脚本后，为每个调用返回的运行时间如下：

Beginning optimisation without parallelisation
Optimisation finished after 59.0 seconds

Beginning optimisation with workers parameter set to 10
Optimisation finished after 60.43 seconds

正如您所看到的，将worker参数设置为10时的执行速度甚至比第一个慢。您能帮我完成这个吗？为了在differential_evolution函数中实现并行化，我还需要做什么吗？
我目前使用的是Python 3.8，而我的scipy版本是1.8.1。