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

Nassir Ibrahim, Sharon Cox, Robert Mills, Andrew Aftelak, Hanifa Shah

Research output: Contribution to journalArticlepeer-review


Multi-objective optimisation (MOOP) methods are used heavily to support decision-makers in addressing problems with con?icting objectives. With global CO2 emission legislation becoming stringent, automotive OEMs face a challenge to balance con?icting commercial and environmental objectives simultaneously. Automotive OEMs seek to maximise pro?ts 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 pur-suing 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 ?rst. 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 ?rst categorised. The systematic literature review reveals that evaluating decision criteria such as the vehicle ?eet portfolio, customer demand, market requirements and ?nancial cost can assist auto-motive OEMs select the optimal CO2 management decision in a given scenario. Next, recon?guring vehicle features, investing in technology, restricting sales and paying CO2 tariffs are identi?ed 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 impli-cations 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.
Original languageEnglish
JournalJournal of Cleaner Production
Publication statusPublished (VoR) - 23 Jun 2021


  • CO2 tariff minimisation Profit maximisation Financial cost Multi-objective optimisation Decision support model Automotive OEMs


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