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Md Arif Hossain

Mathematics | Operations Research | Optimization | Data-Driven Decision Analytics


About Me

I am a Mathematics graduate from Shahjalal University of Science and Technology (SUST) and currently work as a Business Intelligence Analyst in the manufacturing industry.

My research interests lie in:

  • Operations Research
  • Mathematical and Combinatorial Optimization
  • Mixed-Integer Programming
  • Facility Location and Routing
  • Transportation and Logistics Optimization
  • Network Optimization
  • Data-Driven Optimization
  • Machine Learning for Decision-Making

My background combines mathematical research, computational modelling, optimization, and industrial decision analytics. I am particularly interested in developing rigorous optimization methods for complex operational systems and exploring how machine learning can complement mathematical optimization.


Featured Research Project

Geographic Facility Location and Metric Routing Optimization in Poland

This project studies facility-location and routing decisions using mathematical optimization and approximation algorithms.

Key components include:

  • Minimum set-covering formulation for geographic facility placement
  • Exact metric Traveling Salesman Problem formulations
  • Degree and subtour-elimination constraints
  • Iterative constraint-generation approaches
  • Christofides' approximation algorithm
  • Minimum spanning trees and minimum-weight perfect matching
  • Comparison of approximation and exact optimization solutions

Tools: Python, Gurobi, PuLP, SciPy/HiGHS, NetworkX

View Project Repository


Research Background

Matrix Methods for Posets and Lattices

Research conducted through the SUST Research Center on matrix-based approaches to combinatorial structures involving partially ordered sets and lattices.

Tools: MATLAB, Mathematical Modelling, Combinatorial Mathematics

Undergraduate Thesis

On the Determinant, Inverse, and Eigenvalues of Infinite Matrices

Worked on numerical and computational aspects of infinite matrices, including convergence, matrix functions, series expansions, eigenvalues, and numerical approximation.


Applied Decision Analytics

As a Business Intelligence Analyst, I work on quantitative decision-support problems involving:

  • Production capacity and resource allocation
  • Machine utilization and downtime
  • Manufacturing efficiency
  • Scenario and what-if analysis
  • Production planning
  • Predictive modelling
  • Operational performance analysis

These experiences have strengthened my interest in applying Operations Research to real-world decision systems.


Technical Skills

Optimization & Mathematical Modelling
Gurobi • PuLP • SciPy/HiGHS • NetworkX • Mixed-Integer Programming • Combinatorial Optimization • Facility Location • Routing

Scientific Computing & Programming
Python • MATLAB • R • C++ • Fortran • SQL • NumPy • SciPy • pandas

Machine Learning
scikit-learn • PyTorch • TensorFlow/Keras • Predictive Modelling • Classification • Model Evaluation

Analytics & Visualization
Tableau • Power BI • Excel

Research & Development Tools
Git • GitHub • Jupyter • Google Colab • LaTeX • Streamlit


Selected Research & Presentations

  • Rubik's Cube – An Application of Group Theory
    International Conference on Science, Technology, Engineering, Mathematics, and Education, 2023

  • The Alternative Form of the Order of an Element in a Group Under Addition Modulo
    International Conference on Science, Technology, Engineering, Mathematics, and Education, 2023

  • Fine-Grained Classification of Depression, Loneliness, and Fear in Bangla Social Media Text
    ICCIT 2026 — Submitted



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