Mingyao Qi

The software and data in this repository are a snapshot of the software and data that were used in the research reported on in the paper Urban Delivery with a Coordinated Fleet of Trucks and Drones by W. Zeng, H. Yang, H. Wang, and M. Qi.

1. In today’s competitive markets, new entrants who aim to gain market share must strategically optimize their facility location decisions. This challenge, known as the competitive facility locatio...

1 IntroductionThe booming popularity of on-demand delivery services prompts the on-demand supermarkets and grocery retailers, including Sam’s Club, China Resources Vanguard, Freshippo, and Whole Fo...

In “Sequential Competitive Facility Location: Exact and Approximate Algorithms,” Qi et al. consider a competitive facility location problem (CFLP), where two firms sequentially open new facilities within their budgets and maximize their market shares of demand following a probabilistic choice model. They derive an equivalent, single-level mixed-integer nonlinear program (MINLP) reformulation of the bilevel MINLP and exploit the problem structures to derive valid inequalities based on submodularity and concave overestimation. They also develop an approximation algorithm with a constant approximation guarantee. They further study several extensions of CFLP that have general facility-opening costs, outside competitors, and diverse facility-planning decisions. Their approaches significantly accelerate the computation of CFLP on large-sized instances that have not been solved optimally or even heuristically by existing methods.