Srinivasan Balan

Srinivasan Balan’s research interests are in production-inventory optimization, supply chain risk management, and supply chain engineering. Before coming to NC State University, he worked in the industry for eight years in the automotive, manufacturing, healthcare, agribusiness, and consulting sectors. He authored five refereed journal papers and is a certified Six Sigma Green Belt. He received the voice of the future award and excellence award during his work at Murugappa group and Olam international ltd. His website is www.srinivasanbalan.com.

Research Interests

Srinivasan’s research focuses on production-inventory optimization problems. Multi-period capacitated production inventory problems are numerically challenging and computationally intensive. These problems have been researched extensively, and various approximations to solve them have been proposed. In this thesis, unlike classic inventory models, we use a concave, monotonically non-decreasing clearing function (CF) for replenishment. Clearing functions are meta-models that capture the queuing behavior and relationship between the workload and the production in the capacitated production system. Despite various stochastic approximation methods available in the literature, they are not tested against an exact benchmark solution, which prevents rigorous assessment of the quality of their solutions relative to optimality. To gain initial insight, we start by considering the single-period version of the problem, where all production from the period can be used to meet the current period’s demand; hence a single-period lead time zero model. Since the single-period problem is the building block for the multi-period problem, we then develop an exact solution for the multiple-period problem using a stochastic dynamic programming method to obtain a benchmark for all approximation methods to illustrate the optimality gap and quality of the policy.

Education

Publications

Bluemink, B., de Kok, A.G., Srinivasan, B. and Uzsoy, R., 2019, December. Evaluating mixed-integer programming models for solving stochastic inventory problems. In 2019 Winter Simulation Conference (WSC) (pp. 1696-1707). IEEE.

Using simulation for process re-engineering in refractory ceramics manufacturing – a case study
   Balan, S. (2017), The International Journal of Advanced Manufacturing Technology, 93(5-8), 1761-1770.

Multi-response optimization using Grey relational analysis and Shainin design of experiments
   Balan, S. (2015), International Journal of Quality Engineering and Technology, 5(1), 57-78.

An Integrative supplier selection model using Taguchi loss function, TOPSIS and multi-criteria goal programming
   Balan, S., & Sanjay, S. (2013), Journal of Intelligent Manufacturing, 24(6), 1123-1130.