sudhan-bhattarai

CVRPTW_MILP

Solving a Capacitated Vehicle Routing Problem with time windows constraints (CVRPTW) with Mixed Integer Linear Programming (MILP) in python-gurobi API.

HHCRP-1_problem_from_literature

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.

HHCRP-2_new_model

Multi-period Home Healthcare Routing Problem (HHCRP) with qualification, synchronization and time windows constraints.

kMeans_clustering_from_scratch

K means clustering algorithm from scratch to solve a facility location problem (FLP).

Linear_Regression_Polynomial_Fit

Linear Regression with non-linear features input using polynomial transformation.

Linear_Regression_vs_Deep_Neural_Network

Comparing a deep neural network (DNN) model with a linear regression (LR) model to forecast demand for an elderly care facility.

Machine_Learning_01Classification_scikit-learn

Comparing Logistic regression, Support vector machine, Decision tree, Random forest and Gradient Boosting models for binary classification ML problem using scikit-learn.

Simulated_Annealing_Travelling_Salesman_Problem

Using Simulated Annealing (SA) algorithm to improve an initial solution from Nearest Neighbor Search (NNS) for Travelling Salesman Problem (TSP).

two_stage_VS_multi_stage_stochastic_programming

Solving a discrete stochastic programming optimization problem by

WinterModel_TimeSeries

A time series forecast using winter model for a seasonal data.

sudhan-bhattarai/CVRPTW_MILP

Solving a Capacitated Vehicle Routing Problem with time windows constraints (CVRPTW) with Mixed Integer Linear Programming (MILP) in python-gurobi API.

sudhan-bhattarai/HHCRP-1_problem_from_literature

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.

sudhan-bhattarai/two_stage_VS_multi_stage_stochastic_programming

Solving a discrete stochastic programming optimization problem by

sudhan-bhattarai/HHCRP-2_new_model

Multi-period Home Healthcare Routing Problem (HHCRP) with qualification, synchronization and time windows constraints.

sudhan-bhattarai/kMeans_clustering_from_scratch

K means clustering algorithm from scratch to solve a facility location problem (FLP).

sudhan-bhattarai/Simulated_Annealing_Travelling_Salesman_Problem

Using Simulated Annealing (SA) algorithm to improve an initial solution from Nearest Neighbor Search (NNS) for Travelling Salesman Problem (TSP).

sudhan-bhattarai/Linear_Regression_Polynomial_Fit

Linear Regression with non-linear features input using polynomial transformation.

sudhan-bhattarai/Linear_Regression_vs_Deep_Neural_Network

Comparing a deep neural network (DNN) model with a linear regression (LR) model to forecast demand for an elderly care facility.

sudhan-bhattarai/Machine_Learning_01Classification_scikit-learn

Comparing Logistic regression, Support vector machine, Decision tree, Random forest and Gradient Boosting models for binary classification ML problem using scikit-learn.

sudhan-bhattarai/WinterModel_TimeSeries

A time series forecast using winter model for a seasonal data.

sudhan-bhattarai/01Knapsack_Dynamic_Programming

Using Dynamic Programming (DP) method to optimize a 0/1 Knapsack Problem for Amazon shopping list.

sudhan-bhattarai/Incomplete_project--Convolutional_Neural_Network_chest_Xrays

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.

sudhan-bhattarai/Linear_Regression_from_scratch--Y-equals-b0-plus-b1X

Linear regression from scratch with the statictical (least squares) & the gradient descent methods.

sudhan-bhattarai/MIMIC-III

A Neural Network Mode to Forecast Patients’ Length of Stay In A Hospital.

sudhan-bhattarai/MM1_Queue_Simulation

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.

sudhan-bhattarai/quadratic_curve_fitting

Curve fitting using Gurobi/Python

sudhan-bhattarai/Recurrent_Neural_Network_Natural_Language_Processing

Recurrent Neural Network to model Natural Language data with categorical output. Application: predicting side effects and effectiveness of a drug from user review data.

sudhan-bhattarai/sudhan-bhattarai.github.io