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Sushil Raj Poudel 

Sushil Raj Poudel is a Ph.D. candidate in the Department of Industrial and Systems Engineering at Mississippi State University. He is majoring in industrial engineering with the concentration on operations research. He received his bachelor’s degree (in 2013) in industrial and systems engineering with a minor in mathematics from Mississippi State University. Sushil's research interests are in supply chain optimization with application in renewable energy, stochastic programming, multimodal transportation network, and disruption management. He is currently working on drone routing problem in order to survey the disaster affected zone. Sushil is an ex-president of INFORMS Student Chapter at MSU and advisor of Nepalese Student Association at MSU. He enjoys photography, painting, mountain biking, and writing poems on his leisure time. 

MY LATEST RESEARCH

We have used a prediction model to predict the supply of cornstover and solved the two-stage stochastic problem to minimize the total expected system costs for biomass supply chain for co-firing.

Sample Average Approximation (SAA) has been used to circumvent the computational difficulties associated with large scenario stochastic programming problem. We further added the Progressive Hedging(PH) some heuristic approach and Rolling Horizon (RH) to enhance the computational efficiency of the algorithm. The comparison between the results of the proposed approaches shows that the addition of PH, heuristics and RH gradually increased the efficiency of the computation. For example : to solve 40 scenario problem with 5 replication CPLEX and PH went out of memory. PH with heuristics added was able to solve to it's optimality gap of 0.90\% in 9960 CPU times, while PH with heuristics and RH was able to solve to it's optimality gap of 0.00\% in 9900 CPU times.

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