Name: Sudhan Bhattarai
Type: User
Company: Clemson University
Bio: PhD candidate of Industrial Engineering at Clemson University, Clemson, SC.
Optimization | Optimization under uncertainty | Data Science
Location: Clemson, SC, USA 29631
Blog: sudhan-bhattarai.github.io
Sudhan Bhattarai's Projects
Using Dynamic Programming (DP) method to optimize a 0/1 Knapsack Problem for Amazon shopping list.
Solving a Capacitated Vehicle Routing Problem with time windows constraints (CVRPTW) with Mixed Integer Linear Programming (MILP) in python-gurobi API.
Home healthcare routing problem (HHCRP): replication of an algorithm from literature. Solving the master problem of a benders decomposition model of HHCRP using the mixed integer programming (MIP) method.
Multi-period Home Healthcare Routing Problem (HHCRP) with qualification, synchronization and time windows constraints.
Using CNN, DNN and augumented linear output to build three different neural network models to classify the chest diseases from Xrays, numeric inputs and also projecting the prognosis period measure.
K means clustering algorithm from scratch to solve a facility location problem (FLP).
Linear regression from scratch with the statictical (least squares) & the gradient descent methods.
Linear Regression with non-linear features input using polynomial transformation.
Comparing a deep neural network (DNN) model with a linear regression (LR) model to forecast demand for an elderly care facility.
Comparing Logistic regression, Support vector machine, Decision tree, Random forest and Gradient Boosting models for binary classification ML problem using scikit-learn.
A Neural Network Mode to Forecast Patients’ Length of Stay In A Hospital.
Calculate an average wait time in a M/M/1 queue. A M/M/1 model is a single server queuing system with exponential arrival and service times.
Curve fitting using Gurobi/Python
Recurrent Neural Network to model Natural Language data with categorical output. Application: predicting side effects and effectiveness of a drug from user review data.
Using Simulated Annealing (SA) algorithm to improve an initial solution from Nearest Neighbor Search (NNS) for Travelling Salesman Problem (TSP).
Solving a discrete stochastic programming optimization problem by
A time series forecast using winter model for a seasonal data.