Access to food remains a critical issue in Sub-Saharan Africa. In fact, 24.1% of its population suffers from undernourishment, and malnutrition affects more than a third of children under five years old. This problem will be exacerbated as the Sub-Saharan African population is predicted to double by 2050. To address this problem, it is imperative to meaningfully improve accessibility of fruits and vegetables for the population.They are an excellent source of vitamins and minerals that can fight malnutrition. Fruit and vegetable accessibility can be improved by reducing losses, which are estimated on average to be 50%. A literature review shows that there are many areas where solutions can be implemented to reduce these losses. These areas, in order of decreasing occurrence in the literature are: Cold storage, harvesting methods and pre-storage treatments, packaging, transport to markets and the sale stage. The reduction of food waste in SSA involves the establishment of better practices in all these areas. After analysis, it emerges that packaging should generate more interest due to its comparative ease of implementation to support other technologies like cold storage. Packaging made from agricultural waste or non-consumable materials should be highlighted to prevent pollution issues. This solution, in addition to offering a strong potential to fight against pollution, could also increase farmers’ income.

We present a stochastic version of economic tool life models for machines with finite capacity tool magazines and a variable processing speed capability, where the tool life is a random variable. Using renewal theory to express the expected number of tool setups as a function of cutting speed and magazine capacity, we extend previously published deterministic mathematical programming models to the case of minimizing the expected total processing time. A numerical illustration with typical cutting tool data shows the deterministic model underestimates the optimal expected processing time by more than 8% when the coefficient of variation equals 0.3 (typical for carbide tools), and the difference exceeds 15% for single-injury tools having an exponentially distributed economic life (worst case).