Multi-objective decision-making methods for optimising CO2 decisions in the automotive industry. (10th September 2021) - Ibrahim, Nassir; Cox, Sharon; Mills, Robert; Aftelak, Andrew; Shah, Hanifa
Abstract: 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. Highlights: A model for carmakers to maximise profit and minimise CO2 tariffs is established. A cost perspective is adopted to quantify and mitigate impact of CO2 on car sales. Carmaker options to deal with the costs associated with CO2 are categorised. The criteria considered by carmakers in decision-making are synthesised. Decision-making methods and their existing uses are critiqued for their suitability.