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Multi-objective decision-making methods for optimising CO_2 decisions in the automotive industry

机译:用于优化汽车行业中CO_2决策的多目标决策方法

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Multi-objective optimisation (MOOP) methods are used heavily to support decision-makers in addressing problems with conflicting objectives. With global CO2 emission legislation becoming stringent, automotive OEMs face a challenge to balance conflicting commercial and environmental objectives simultaneously. Automotive OEMs seek to maximise profits by stimulating global sales volumes whilst also minimising CO2 management costs. MOOP methods can quantify CO2 management costs to optimise decisions in response to the increasingly regulated business environment. Whilst automotive OEMs are modelling the dynamic knock-on effects of pursuing multiple objectives, there is also a need to formulate their decision objectives, decision criteria and decision options to be considered as part of CO2 management decisions first. A systematic literature review offers a detailed account of how automotive OEMs can optimise CO2 management decisions.The multiple decision objectives, decision criteria and CO2 management decision options considered by automotive OEMs are first categorised. The systematic literature review reveals that evaluating decision criteria such as the vehicle fleet portfolio, customer demand, market requirements and financial cost can assist automotive OEMs select the optimal CO2 management decision in a given scenario. Next, reconfiguring vehicle features, investing in technology, restricting sales and paying CO2 tariffs are identified as the most common CO2 management decisions taken by automotive OEMs. Then MOOP methods are critiqued for their suitability, before a novel decision support model, which adopts an automotive OEMs' perspective for mitigating CO2 management costs is proposed. It is found that interactive and objective decision making approaches such as MOOP opposed to classical Multi Criteria Decision Making (MCDM) methods can more precisely quantify the commercial implications of the stricter global CO2 emission legislation now imposed on automotive OEMs. If automotive OEMs adopt the proposed model, they can effectively model future CO2 management scenarios and pre-emptively prevent counter-productive decisions by minimising CO2 management costs.
机译:多目标优化(MOOP)方法大量用于支持决策者解决与跨越目标的问题。随着全球二氧化碳排放立法变得严格,汽车OEM在同时平衡商业和环境目标的平衡面临挑战。汽车OEM通过刺激全球销售量来最大限度地促使二氧化碳管理成本最大限度地提高利润。 MOOP方法可以量化CO2管理成本,以优化响应日益监管的商业环境的决策。虽然汽车OEM正在为追求多目标的动态敲门作用,但也需要制定其决定目标,决策标准和决定选项首先被视为二氧化碳管理决定的一部分。系统文献综述详细说明了汽车OEM如何优化二氧化碳管理决策的详细说明。汽车OEM审议的多项决定目标,决策标准和二氧化碳管理决定选项首先进行分类。系统文献综述表明,评估车队组合,客户需求,市场要求和财务成本等决策标准可以帮助汽车OEM在特定情况下选择最佳二氧化碳管理决策。接下来,重新配置车辆特征,投资技术,限制销售和支付二氧化碳关税被确定为汽车OEM所采取的最常见的二氧化碳管理决策。然后,在采用新型决策支持模型之前,将莫波普方法批评,以提出采用汽车OEM的汽车OEM的透视,以减轻二氧化碳管理成本。有人发现,与经典多标准决策(MCDM)方法相反的摩普赛的互动和客观决策方法可以更精确地量化现在强加于汽车OEM的更严格的全球二氧化碳排放法的商业影响。如果汽车OEM采用拟议的模型,他们可以通过最大限度地降低二氧化碳管理成本,有效地模拟未来的二氧化碳管理情景,并先发制地防止反复化的决策。

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