The in-flight catering industry is a major contributor to food wastage. This wastage is a direct result of the deliberate overproduction of in-flight meals to protect against meal shortages and dissatisfied passengers. With the global strive towards sustainability and the resulting impact of wastage on a company's corporate image, in-flight catering companies need a solution that strives to achieve zero waste and a 100% passenger satisfaction level. This dissertation evaluates the value of combining product substitution and 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 decision-making model's purpose is to assist in-flight caterers to make improved decisions regarding the quantity of each meal type to produce for the specific flight under consideration. The model developed is defined as a stochastic multi-objective mixed-integer programming model with fixed recourse and two-way, stock-out based, partial consumer-driven (static) product substitution. The model relies on the output of a forecasting model, that consists of a time-inhomogeneous Markov Chain and a multiple regression model, to forecast the probability distribution of a flight's aggregate meal demand. Due to the lack of available data from public sources, synthetic data is generated to evaluate the model developed. The model is compared against three alternative models that lack 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 the passenger load uncertainty improves the model's average reliability to achieve a 92% minimum passenger satisfaction level with at least 9.2%. Furthermore, it is shown that the stochastic passenger load model produces an average of 2.2 fewer surplus meals per flight instance at the expense of a 3.3% lower reliability when including the substitution behaviour of passengers. This substitution model's superior waste minimisation is attributed to the model's inherent risk-pooling capabilities, and further analysis shows that the value of product substitution increases when the model becomes more constrained. It is, therefore, concluded that the value of product substitution depends on the in-flight caterer's bias towards maximising either reliability or performance. / Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2021. / Council for Scientific and Industrial Research (CSIR) / Industrial and Systems Engineering / MEng / Unrestricted