Abstract
In-flight caterers are faced with an immense challenge of catering for each passenger on-board a flight without knowing the flight’s final passenger load or the meal preferences of its passengers. These uncertainties lead to excessive amounts of waste generation because in-flight caterers tend to over-produce meals to mitigate the risk of meal shortages and dissatisfied passengers. This paper evaluates the value of combining product substitution and meal demand uncertainty within an inventory decision-making model as a potential solution opportunity for the wastage dilemma faced by the in-flight catering industry. The model developed is defined as a stochastic and multi-objective mixed-integer programming model with fixed recourse and static product substitution. The model relies on the output of a time-inhomogeneous Markov Chain forecasting model with a multiple regression analysis to forecast the probability distribution of the flight’s aggregate meal demand. Due to the lack of available data from public sources, synthetic data was generated to evaluate the model developed. The model was compared against three alternative models that lacked either demand uncertainty, product substitution or both to validate the value of including these elements in the decision-making model. The comparison results indicate that the inclusion of passenger load uncertainty improves the model’s reliability to a achieve the pre-defined minimum passenger satisfaction level, whereas the inclusion of product substitution improves the model’s waste minimisation capabilities at the expense of a slightly lower reliability. To the authors’ best knowledge, no previous study has attempted to exploit the risk-pooling capabilities of a substitution model to minimise wastage resulting from surplus in-flight meals.
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