The research was intended to describe the design and evaluation of strategies for the aggregate planning of a company dedicated to the manufacture of fish canned goods. To this end, descriptive research was carried out with a longitudinal non-experimental design. The results demonstrated a high variability in the behaviour of sales, typical of the Peruvian fishing sector, and when analyzing different forecast alternatives it was chosen to use a series breakdown, with a multiplicative model and seasonal length of 6 periods; which presented the lowest absolute average percentage error compared to other quantitative methods. The initial evaluation of the aggregate plans determined that a demand pursuit strategy generated the lowest value of total costs, as it was estimated at $334,957; while the leveling strategy reached a value of $385,275 and the use of an overtime strategy amounting to $376,056. Similarly, plans were evaluated using production ratios and it was determined that a demand pursuit strategy would employ $2.33 per cash produced, while overtime and leveling plans had higher amounts and would reach between $2.37 and $2.63 per cash produced, respectively. On the other hand, simulations by Monte Carlo's method showed that in 10,000 different sales scenarios, there was a 95.10% chance that, following a demand pursuit strategy, costs do not exceed $311,753. In addition, a further 10,000 random sales cases were simulated and it was established that the pursuit plan, in contrast to the overtime strategy, would generate lower costs per cash produced, with a 95.04% probability that the difference will exceed the $0.05/cash produced. Finally, through a design and evaluation of strategies for aggregate planning, it was concluded that a demand pursuit strategy would optimize production costs in a company dedicated to the manufacture of fish canned in Ancash - Peru.