3 citations · 7 across the 14 of their papers we have counts for
16 papers
Algorithms for min-buying in networks
Aaditya Bhardwaj, Ben Black, Trivikram Dokka +1
The paper is motivated by pricing decisions faced by forecourt fuel retailers across their outlets on a road network. Through our modelling approach we are able adapt the network s…
Parametric Distributionally Robust Optimisation Models for Budgeted Multi-period Newsvendor Problems
Ben Black, Trivikram Dokka, Christopher Kirkbride
In this paper, we consider a static, multi-period newsvendor model under a budget constraint. In the case where the true demand distribution is known, we develop a heuristic algori…
Robust Markov decision processes under parametric transition distributions
Ben Black, Trivikram Dokka, Christopher Kirkbride
This paper considers robust Markov decision processes under parametric transition distributions. We assume that the true transition distribution is uniquely specified by some param…
Pricing and Electric Vehicle Charging Equilibria
Trivikram Dokka, Jorge Bruno, Sonali SenGupta +1
We study equilibria in an Electric Vehicle (EV) charging game, a cost minimization game inherent to decentralized charging control strategy for EV power demand management. In our m…
Data-driven Heuristics for DC optimal transmission switching problem
Juncheng Li, Trivikram Dokka, Guglielmo Lulli +1
The goal of Optimal Transmission Switching (OTS) problem for power systems is to identify a topology of the power grid that minimizes the cost of the system operation while satisfy…
Distributionally Robust Resource Planning Under Binomial Demand Intakes
Ben Black, Russell Ainslie, Trivikram Dokka +1
In this paper, we consider a distributionally robust resource planning model inspired by a real-world service industry problem. In this problem, there is a mixture of known demand…
Understanding controlled EV charging impacts using scenario-based forecasting models
Rahul Roy, Trivikram Dokka, David A. Ellis +2
Electrification of transport is a key strategy in reducing carbon emissions. Many countries have adopted policies of complete but gradual transformation to electric vehicles (EVs).…
Automatic Generation of Algorithms for Black-Box Robust Optimisation Problems
Martin Hughes, Marc Goerigk, Trivikram Dokka
We develop algorithms capable of tackling robust black-box optimisation problems, where the number of model runs is limited. When a desired solution cannot be implemented exactly t…
An Efficient Approach to Distributionally Robust Network Capacity Planning
Trivikram Dokka, Francis Garuba, Marc Goerigk +1
In this paper, we consider a network capacity expansion problem in the context of telecommunication networks, where there is uncertainty associated with the expected traffic demand…
Particle Swarm Metaheuristics for Robust Optimisation with Implementation Uncertainty
Martin Hughes, Marc Goerigk, Trivikram Dokka
We consider global non-convex optimisation problems under uncertainty. In this setting, it is not possible to implement a desired solution exactly. Instead, any other solution with…
The Multi-level Bottleneck Assignment Problem: Complexity and Solution Methods
Trivikram Dokka, Marc Goerigk
We study the multi-level bottleneck assignment problem (MBA), which has important applications in scheduling and quantitative finance. Given a weight matrix, the task is to rearran…
Approximate policy iteration using neural networks for storage problems
Trivikram Dokka, Richlove Frimpong
We consider the stochastic single node energy storage problem (SNES) and revisit Approximate Policy Iteration (API) to solve SNES. We show that the performance of API can be booste…
Mixed Uncertainty Sets for Robust Combinatorial Optimization
Trivikram Dokka, Marc Goerigk, Rahul Roy
In robust optimization, the uncertainty set is used to model all possible outcomes of uncertain parameters. In the classic setting, one assumes that this set is provided by the dec…
Algorithms and Uncertainty Sets for Data-Driven Robust Shortest Path Problems
André Chassein, Trivikram Dokka, Marc Goerigk
We consider robust shortest path problems, where the aim is to find a path that optimizes the worst-case performance over an uncertainty set containing all relevant scenarios for a…
Robust toll pricing: A novel approach
Trivikram Dokka, Alain B. Zemkoho, Sonali Sen Gupta +1
We study a robust toll pricing problem where toll setters and users have different level of information when taking their decisions. Toll setters do not have full information on th…
An Experimental Comparison of Uncertainty Sets for Robust Shortest Path Problems
Trivikram Dokka, Marc Goerigk
Through the development of efficient algorithms, data structures and preprocessing techniques, real-world shortest path problems in street networks are now very fast to solve. But…