About me

Hi! I'm Ravit Pichayavet, a Ph.D. candidate in Supply Chain Engineering at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) . His research, advised by Professor Alan Erera, focuses on the optimization of high-velocity logistics, specifically within middle-mile and last-mile operations. Ravit specializes in developing data-driven models and large-scale optimization technology for routing, scheduling, and resource allocation. His work involves close collaborations with industry partners, leveraging large-scale commercial datasets to solve complex, real-world logistics challenges. You can also find my studying status on ISyE students page.

My recent CV (last updated on Mar 1 2026).

Ph.D. Thesis Topic: Data-Driven Optimization of High-Velocity Logistics Systems: Addressing Challenges from Last-mile Delivery to Middle-mile Freight Management

with major in Supply Chain Engineering and minor in Computation and Machine Learning

Expected Graduation: Spring - Summer 2026

Industry Experience

Applied Scientist Intern

Middle Mile Science, LTL Team

AMAzon, Bellevue, WA |

May 2025 - Aug 2025

Designed and implemented a routing optimization module (e.g., Mixed-Integer Programming, Column generation, Routing heuristics) to improve the efficiency of LTL freight movement in Amazon middle-mile network

Teaching Experience

Graduate Student Instructor

ISyE 3103: Supply Chain Modeling: Logistics

| Spring 2026

Serving as the Instructor for an undergraduate course ISyE3103, delivering lectures on inventory management, freight transportation, and supply chain network design

PhD Research Projects

An icon showing graph and magnifying glass representing data analysis and prediction.

Demand Prediction and Transportation Resource Allocation Problem

Michelin North America |

Georgia Tech, Atlanta, GA |

July 2024 - present

Analyze demand patterns and formulate a model to optimize shipment planning by reserving and purchasing shipping services from trucking carriers

A cute moving pot on stove representing cooking action (under development)

Ongoing work...

Improvement Heuristics for Extremely Large-Scale LTL Flow and Load Planning

UPS |

Georgia Tech, Atlanta, GA |

July 2022 - Present

Develop a local search heuristic tool for an extremely large-scale flow and load planning problem (LTL-Service Network Design)
Design and implement greedy improvement heuristics that iteratively search for best marginal reflowing improvement across the network

Presented at INFORMS Annual Meeting 2024

Seattle, WA |

OCTober 20 - 23, 2024 |

CONTACT FOR SLIDE

An icon of motor bike and its delivery route representing last-mile delivery

Rate-based Vehicle Routing Problem for Delivery in Densely Populated Urban Areas

SF Express |

Georgia Tech, Atlanta, GA |

July 2021

Consider the intermediate echelon of the city logistic network, where packages are transferred between a local hub to micro hubs or parcel lockers
Develop a steady state rate-based vehicle routing model for fleet size and route planning
Solve set-partitioning routing model using Column Generation algorithm where the pricing is the Resource Constrained Shortest Path Problem (RCSPP) solved by dynamic programming (DP)

Presented at INFORMS TSL Second Triennial Conference 2023

Chicaco, IL |

July 23 - 26, 2023 |

CONTACT FOR SLIDE