Combinatorial optimization problems are frequently encountered in a variety of applications including telecommunications, computer networks, transportation, supply chain and logistics. They are often hard to solve due to the presence of integer variables. Commercial software like CPLEX cannot solve these problems for realistic and large instances unless problem-specific algorithms are developed and integrated to their default functions. I consider the design of a content delivery network (CDN) that maintains multiple data hubs for efficient service and reduced delivery cost. Many decision problems (for example, location of hubs, allocation of data to these hubs, user assignment, query routing and network design) appear in this framework and they are inter-dependant. The model and formulation to find the solutions to each of these problems in an integrated manner is a computationally challenging task. Therefore, the focus is on algorithm development for this kind of large scale optimization problem.
Discrete Particle Swarm Optimization Algorithms for Two Variants of the Static Data Segment Location Problem by Sen G., Krishnamoorthy M. Applied Intelligence 0-0 (Accepted/In-Press)
A Benders Decomposition Approach for Static Data Segment Location to Servers Connected by a Tree Backbone by G Sen, M Krishnamoorthy, V Narayanan, N Rangaraj Operations Research Proceedings - (2015)
Mathematical models and empirical analysis of a simulated annealing approach for two variants of the static data segment allocation problem by Sen G., Krishnammoorthy M. , Narayanan V. , Rangaraj N. Networks 68 4-22 (2016)
Exact approaches for static data segment allocation problem in an information network by G Sen, M Krishnamoorthy, N Rangaraj, V Narayanan Computers & Operations Research 62 282-295 (2015)
Facility location models to locate data in information networks: a literature review by G Sen, M Krishnamoorthy, N Rangaraj, V Narayanan Annals of Operations Research In Press, Springer 1-36 (2015)
Area of Research: Operations Research
Area of Research: Safety Analytics