The CK Quarterly introduces working papers from Dr. Changhyun Kwon and STOM Lab in each season, four times a year. Issues will cover various topics in operations research, optimization, transportation systems, and service operations. This series started in Winter 2014. Dr. Kwon is currently an associate professor in the Department of Industrial and Management Systems Engineering at the University of South Florida.
Julia is a computer language for scientific computing. This book introduces Julia programming for common tasks in operations research. This book is mainly targetted to first-year graduate students in operations research and related fields, but will also be suitable for advanced undergraduate students and practitioners.
Online Book Link
When drivers' preferences over tolls and time are probabilistic, how should we charge tolls for regulating both hazmat truck drivers and other regular drivers to mitigate the risk from hazmat accidents?
When we design road networks, we need to predict drivers' new behavior. How should we model such prediction? This paper provides a comprehensive review.
If we allow more roads for hazmat, can we make a safer road network? Should we change the location of hazmat response units accordingly? Would some residents be unhappy with that change? This paper suggests a comprehensive modeling framework to answer these questions.
This paper investigates how we can make the road network safer by regulating hazardous materials transportation via dual toll pricing. The core idea is to charge separate tolls for regular vehicles and hazmat trucks. Computational methods are proposed.
The Julia Langugage is a recently developed programming language for numerical computations.
RobustShortestPath.jl is a package that finds robust shortest paths when travel cost is subject to uncertainty.
TrafficAssignment.jl finds traffic user equilibrium for congested road networks.
How should we determine a safe route for transporting hazardous materials such as explosive and corrosive chemicals? This paper questions existing routing methods in hazmat transportation and proposes a robust and risk-averse routing method.
Most research in hazmat transportation ignore uncertainty in consequences from a hazmat accident. To design a safe road network, this paper considers uncertainty in accident consequences and develops a computational method based on Lagrangian-relaxation.