On Solving Chance-Constrained Models with Gaussian Mixture Distribution

We study linear chance-constrained problems where the coefficients follow a Gaussian mixture distribution. We provide mixed-binary quadratic programs that give inner and outer approximations of the chance constraint based on piecewise linear approximations of the standard normal cumulative density function. We show that $O\left(\sqrt{\ln(1/\tau)/\tau} \right)$ pieces are sufficient to attain $\tau$-accuracy in the chance constraint. … Read more

Optimizing pricing strategies through learning the market structure

This study explores the integration of market structure learning into pricing strategies to maximize revenue in e-commerce and retail environments. We consider the problem of determining the revenue maximizing price of a single product in a market of heterogeneous consumers segmented by their product valuations; and analyze the pricing strategies for varying levels of prior … Read more

Simple and Effective: A Deterministic Auction with Support Information

We study an auction design problem where a seller aims to sell a single item to multiple bidders with independent private values. The seller knows only an upper bound on these values and does not know their distribution. The objective is to devise a deterministic auction mechanism effective across a broad set of distributions. We … Read more

Using Neural Networks to Guide Data-Driven Operational Decisions

We propose to use Deep Neural Networks to solve data-driven stochastic optimization problems. Given the historical data of the observed covariate, taken decision, and the realized cost in past periods, we train a neural network to predict the objective value as a function of the decision and the covariate. Once trained, for a given covariate, … Read more

The Value of Robust Assortment Optimization Under Ranking-based Choice Models

We study a class of robust assortment optimization problems that was proposed by Farias, Jagabathula, and Shah (2013). The goal in these problems is to find an assortment that maximizes a firm’s worst-case expected revenue under all ranking-based choice models that are consistent with the historical sales data generated by the firm’s past assortments. We … Read more

Price Optimization with Practical Constraints

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 … Read more

Robust Price Optimization of Multiple Products under Interval Uncertainties

In this paper, we solve the multiple product price optimization problem under interval uncertainties of the price sensitivity parameters in the demand function. The objective of the price optimization problem is to maximize the overall revenue of the firm where the decision variables are the prices of the products supplied by the firm. We propose … Read more

Randomized Assortment Optimization

When a firm selects an assortment of products to offer to customers, it uses a choice model to anticipate their probability of purchasing each product. In practice, the estimation of these models is subject to statistical errors, which may lead to significantly suboptimal assortment decisions. Recent work has addressed this issue using robust optimization, where … Read more

Product Assortment Competition with the Decoy Effect

The fraction of customers who choose a particular item from among a set of available items can be increased significantly by the inclusion of a related inferior (and apparently irrelevant) item in the choice set. This violation of the independence from irrelevant alternatives and the regularity properties is called the decoy effect, dominance effect, or … Read more

Choice Based Revenue Management for Parallel Flights

This paper describes a revenue management project with a major airline that operates in a fiercely competitive market involving two major hubs and having more than 30 parallel daily flights. The market has a number of unusual characteristics including (1) almost half of customers choose not to purchase the tickets after booking; (2) about half … Read more