Watch this short webinar to learn how to optimize the technician routing and scheduling (TRS) decisions at a telecommunications firm. Example scenarios and solution visualization will be demonstrated.

Webinar Summary

In this session, we will share the latest Jupyter Notebook Modeling Example featuring a Technician Routing & Scheduling Demo. We will showcase a mixed-integer programming model to simultaneously optimize the technician routing and scheduling (TRS) decisions at a telecommunications firm. Example scenarios and solution visualization will be demonstrated.

Presenters

Pano Santos

Dr. Santos is a Sr. Technical Content Manager at Gurobi Optimization. Santos retired from Hewlett-Packard Enterprise as Distinguished Technologist. During his 23 years at HP Labs, he developed and implemented several decision support tools of mathematical programming applications for workforce planning at the services industry, supply chain planning, CRM, transportation and logistics, and operating room Scheduling. Santos has a Bachelor’s degree in applied mathematics from the University of Mexico (UNAM), and a Master and PhD degrees in Operations Research from the University of Waterloo in Canada.

 

Gurobi Days Digital Speaker, Haitao Li

Haitao Li is Professor and Chair of the Supply Chain & Analytics Department, College of Business Administration at University of Missouri – St Louis (UMSL). Dr. Li has extensive research experience in optimization modeling and algorithm design with industry applications in supply chain design, resource planning, vehicle routing and scheduling. His past and ongoing research projects are funded by the Army Research Office, USDOT, ASCM, and HP Labs, Express Scripts and Ameren in the private sector. Dr. Li has published more than 30 peer reviewed journal articles and serves as Associate Editor of the Journal of the Operational Research Society. With two U.S. Patent applications and a number of invention disclosures, he was named 2015 UMSL Inventor of The Year.

 

Dan Jeffrey

Dan Jeffrey has twenty years of professional experience in Math Programming and Data Science, working as a technical product expert and as a consultant. He has architecture and programming expertise with all major computer programming languages, math programming experience with Python, AMPL, and OPL plus programming expertise with the AMPL Solver library. Today, Dan is a MIP Fanatic — working as a member of the Gurobi Support Team.

Presented Materials

You can download the slides presented in this webinar here.