Angelo Mancini

 

Faculty Speaker Angelo Mancini [University of Chicago]
Title Dynamic Release Management: A Market IntensityApproach
Date & Time Thursday, February 26, 2015 at 9:30am
Place UCLA Anderson School of Management 
Room D-310 

 

Abstract
We consider a release manager who sequentially releases new versions of her product by drawing from a fixed and non-replenishable finite set of features while facing an exogenous, stochastically evolving marketplace. In the absence of fixed costs, we provide conditions under which there exists a quasi-open-loop optimal policy, i.e., an optimal policy that depends only on the set of available features and not the state of the external market. Computing such a policy amounts to solving a related deterministic release-sequencing problem, and we apply an exchange argument to obtain an index condition necessary for optimality. In the simplest case we consider, a heuristic based on this condition reduces to an optimal ordering of Gittins indices and is equivalent to the "weighted discounted shortest processing time first" stochastic scheduling rule. However, we prove it is suboptimal by an arbitrarily large margin in other settings. We apply approximate dynamic programming (ADP) to address the case with positive fixed costs by making a novel value function approximation motivated by the case without fixed costs. The resulting policy can provably outperform an intuitive certainty-equivalent heuristic by an arbitrarily large margin, and performs within 3.5% of optimality across a range of numerical trials.

Angelo Mancini