In most cases, prices are inputs to the models.

In some cases, however, determining the price to pay or charge is a decision that the business is making, and therefore one that optimization can assist.  Some of the the most sophisticated pricing changes dynamically, based on how actual consumption matches planned or forecasted consumption.

• For the high frequency hedge fund, the optimization determines how much the fund would be willing to pay for each potential security it can acquire, and what price it would be willing to accept to unwind a position.  These prices change dynamically as the market prices and forecasts for these securities change, as well as the model’s perception of the supply/demand characteristic of each security in real time.
• For the freight railroad, the optimization supports both a commissioned sales force and a self-serve web portal with dynamic pricing.  "Yield management” or “revenue management” techniques are used to provide dynamic pricing designed to maximize profits rather than simply sell off capacity with fixed prices.
• For the service network company, executive management used optimization to combine forecasted demand with the costs of multiple potential service and configuration offerings to determine the maximum revenue and profit potential.