  In this paper, we study a retailer price optimization problem which includes
the practical constraints: maximum number of price changes and minimum amount
of price change (if a change is recommended). We provide a closed-form formula
for the Euclidean projection onto the feasible set defined by these two
constraints, based on which a simple gradient projection algorithm is proposed
to solve the price optimization problem. We study the convergence and solution
quality of the proposed algorithm. We extend the base model to include
upper/lower bounds on the individual product prices and solve it with some
adjustments to the gradient projection algorithm. Numerical results are
reported to demonstrate the performance of the proposed algorithm.
