As global warming becomes increasingly serious, some proper measures should be taken to avoid the possible devastating effects. To address this issue, corporations may take CO2 emission into consideration when they are engaged in operations planning. In this study, we attempt to optimise order fulfilment which considers carbon footprint as well as cost as objectives for global companies with multiple manufacturing sites. A two‐phased decision‐making mechanism is adopted: in the first phase, inappropriate manufacturing sites are manually excluded to reduce computation time; in the second phase, multi‐objective genetic algorithm (MOGA) is employed to find solutions which illustrate the interactions between total carbon footprint and total cost. In order to examine the effectiveness of the proposed approach, this study performs a variety of experiments partly based on real data from a famous global company in Taiwan. The research findings show that the proposed mechanism can obtain feasible solutions effectively and efficiently. When the site number increases, the total carbon footprint decreases, and influences the environment positively.
