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B.Sc. Final Project — IAF Resource Optimization (Grade 92, Shenkar)

Live Project Demo

Interactive Dashboard (Base44)runs on fully synthesized data, re-skinned as a fictional civilian company per military information-security requirements.

Project Overview

Crew-scheduling optimization for Israeli Air Force (IAF) squadrons, developed during the "Iron Swords" war. A full operational year — 52 weeks, 39,000+ crew assignments, ~120 aircrew members — was analyzed to replace manual Excel-based scheduling with a data-driven decision-support system, powered by a linear-programming assignment model and an interactive prototype for squadron commanders.

My role: Technical lead of the project — data analysis, optimization-model formulation, and development of the Base44 decision-support prototype.

Key Features & Methodology

  • Operations Research: Binary linear-programming assignment model — 3 objective functions and 9 hard-constraint families (qualifications, medical fitness, availability, rest intervals, workload caps, instructor pairing); full formulation in the report.
  • Exploratory Data Analysis: ~3× weekly load swings (444 → 1,202 assignments), 28.8% of crew-week capacity left unassigned, and workload gaps of up to 14 vs. 2 tasks per crew member.
  • Statistical Analysis: Pearson correlation (SciPy) between weekly workload and ~1,000 recorded mis-assignments (52% qualification / 48% availability) — r≈0.72–0.76.
  • KPI Definition: Quantified targets — a 30% cut in unassigned crew (baseline: 34.5/week), ≤5 qualification errors/week (baseline: 9.8), and a ≥20% gain in user satisfaction.
  • Field Validation: 8 in-depth role-holder interviews, a benchmark against 4 academic studies, and 3 commander feedback sessions.

Tools & Technologies

Python (Pandas, NumPy, SciPy, Seaborn, Matplotlib) · Base44 · Operations Research (Linear Programming), Statistical Analysis, Process Improvement

Repository Content

  • quantitative_data_analysis.ipynb: Data cleaning, trend visualization, error profiling, and correlation analysis (heatmap, regression scatters).
  • operational_metrics_data.xlsx: Anonymized dataset — 52 weekly records, 12 monthly aggregates, and a statistical-summary sheet.
  • Project_Final_Report.pdf: Full academic report (Hebrew + English executive summary) — methodology, findings, complete model formulation, and commander feedback.

About

Final Project (Grade 92, B.Sc. IE&M, Shenkar): crew-scheduling optimization for IAF squadrons during the Iron Swords war — 52 weeks / 39K+ assignments analyzed, a linear-programming assignment model, and a live Base44 decision-support prototype targeting a 30% cut in unassigned crew

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