The Tinkan Company produces 1-pound cans for the Canadian salmon industry. Each year, the salmon spawn during a 24-hour period and must be canned immediately. Tinkan has the following agreement with the salmon industry. The company can deliver as many cans as it chooses. Then the salmon are caught. For each can by which Tinkan falls short of the salmon industry’s needs, the company pays the industry a $2 penalty. Cans cost Tinkan $1 to produce and are purchased for $2 per can. If any cans are left over, they are returned to Tinkan and the company reimburses the industry $2 for each extra can. These extra cans are put in storage for next year. Each year a can is held in storage, a carrying cost equal to 20% of the can’s production cost is incurred. It is well known that the number of salmon harvested during a year is strongly related to the number of salmon harvested the previous year. In fact, using past data, Tinkan estimates that the harvest size in year t, Ht (measured in the number of cans required), is related to the harvest size in the previous year, Ht–1, by the equation Ht
Ht1et where et is normally distributed with mean 1.02 and standard deviation 0.10.

Tinkan plans to use the following production strategy.

For some value of x, it will produce enough cans at the beginning of year t to bring its inventory up to x ˆHt, where ˆHt is the predicted harvest size in year t.

Then it will deliver these cans to the salmon industry.

For example, if it uses x
100,000, the predicted harvest size is 500,000 cans, and 80,000 cans are already in inventory, then Tinkan will produce and deliver 520,000 cans. Given that the harvest size for the previous year was 550,000 cans, use simulation to help Tinkan develop a production strategy that will maximize its expected profit over the next 20 years.