首页> 外文OA文献 >Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles
【2h】

Sim-heuristics low-carbon technologies’ selection framework for reducing costs and carbon emissions of heavy goods vehicles

机译:模拟启发式低碳技术的选择框架,用于降低重型货车的成本和碳排放

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。
获取外文期刊封面目录资料

摘要

UK logistics fleets face increasing competitive pressures due to volatile fuel prices and the small profit margins in the industry. By reducing fuel consumption, operational costs and carbon emissions can be reduced. While there are a number of technologies that can reduce fuel consumption, it is often difficult for logistics companies to identify which would be the most beneficial to adopt over the medium and long terms. With a myriad of possible technology combinations, optimising the vehicle specification for specific duty cycles requires a robust decision-making framework. This paper combines simulated truck and delivery routes with a metaheuristic evolutionary algorithm to select the optimal combination of low-carbon technologies that minimise the greenhouse gas emissions of long-haul heavy goods vehicles during their lifetime cost. The framework presented is applicable to other vehicles, including road haulage, waste collection fleets and buses by using tailored parameters in the heuristics model.
机译:由于燃油价格波动和行业利润微薄,英国物流船队面临越来越大的竞争压力。通过减少燃料消耗,可以降低运营成本和碳排放量。尽管有许多技术可以降低燃油消耗,但物流公司通常很难确定哪种技术在中长期内最有利。在无数可能的技术组合下,针对特定占空比优化车辆规格需要强大的决策框架。本文将模拟卡车和运输路线与元启发式进化算法结合在一起,以选择低碳技术的最佳组合,从而将长途重型货车在其使用寿命期间的温室气体排放降至最低。通过使用启发式模型中的定制参数,提出的框架适用于其他车辆,包括公路运输,垃圾收集车队和公共汽车。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号