Open Access. Powered by Scholars. Published by Universities.®
Operations Research, Systems Engineering and Industrial Engineering Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
An Exponential Cone Programming Approach For Managing Electric Vehicle Charging, Li Chen, Long He, Yangfang (Helen) Zhou
An Exponential Cone Programming Approach For Managing Electric Vehicle Charging, Li Chen, Long He, Yangfang (Helen) Zhou
Research Collection Lee Kong Chian School Of Business
To support the rapid growth in global electric vehicle adoption, public charging of electric vehicles is crucial. We study the problem of an electric vehicle charging service provider, which faces (1) stochastic arrival of customers with distinctive arrival and departure times, and energy requirements as well as (2) a total electricity cost including demand charges, costs related to the highest per-period electricity used in a finite horizon. We formulate its problem of scheduling vehicle charging to minimize the expected total cost as a stochastic program (SP). As this SP is large-scale, we solve it using exponential cone program (ECP) approximations. …
Robust Two-Stage Stochastic Linear Programs With Moment Constraints, Sarah Yini Gao, Lingchen Kong, Jie Sun
Robust Two-Stage Stochastic Linear Programs With Moment Constraints, Sarah Yini Gao, Lingchen Kong, Jie Sun
Research Collection Lee Kong Chian School Of Business
We consider the two-stage stochastic linear programming model, in which the recourse function is a worst case expected value over a set of probabilistic distributions. These distributions share the same first- and second-order moments. By using duality of semi-infinite programming and assuming knowledge on extreme points of the dual polyhedron of the constraints, we show that a deterministic equivalence of the two-stage problem is a second-order cone optimization problem. Numerical examples are presented to show non-conservativeness and computational advantage of this approach.