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首页> 外文期刊>Journal of ambient intelligence and humanized computing >Solving the green-fuzzy vehicle routing problem using a revised hybrid intelligent algorithm
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Solving the green-fuzzy vehicle routing problem using a revised hybrid intelligent algorithm

机译:使用改进的混合智能算法解决绿色模糊车辆路径问题

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摘要

Green logistics is an emerging area in supply chain management, which has been shown to have tremendous impacts in recent years to face the serious climate changes risks. In this paper, the fuel consumption and fuzzy travel time have been delineated in developing and solving the green-fuzzy vehicle routing problem as an extension of the celebrated VRP in which routes are performed to reduce the total expenditure. Different from the existing solution manners, we transform the original fuzzy chance constrained programming model into an equivalent deterministic model, and then revise the original hybrid intelligent algorithm by replacing the embedded fuzzy simulation with analytical function calculation. Finally, a comparative study with the corresponding literature is performed, which shows that the revised algorithm can not only improve the solution accuracy but also shorten the runtime greatly.
机译:绿色物流是供应链管理中的新兴领域,近年来已显示出巨大的影响,以应对严重的气候变化风险。在本文中,在开发和解决绿色模糊车辆路径问题时,已对油耗和模糊行驶时间进行了描述,这是著名的VRP的扩展,在该方法中,执行路线以减少总支出。与现有的求解方式不同,我们将原始的模糊机会约束规划模型转换为等效的确定性模型,然后通过将嵌入的模糊仿真替换为解析函数计算来修改原始的混合智能算法。最后,与相关文献进行了比较研究,结果表明,改进后的算法不仅可以提高求解精度,而且可以大大缩短运行时间。

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