This paper describes the possibility of applying a generic, cloud-based Optimisation as a Service facility to food cooking planning and scheduling in a commercial kitchen. We propose a chromosome encoding and customisation of the classic MOEA/D multi-objective genetic algorithm. The applicability of the proposed approach is evaluated experimentally for two scenarios different with respect to the number of cooking appliances and the amount of the ordered food. The proposed system managed to determine the trade-offs between cooking time, energy dissipation and food quality.