erlang-c

A bare bone implementation of Erlang C in Python. No external modules/libraries we're used. Everything was derived directly from the formula.

Queueing-theory math for the economics of scale: Erlang B/C, M/M/c latency percentiles, pool consolidation, and square-root staffing. Zero-dependency, edge-safe TypeScript.

Forecast 30-minute contact-centre call volumes and turn demand into queue-level staffing recommendations with XGBoost, FastAPI, Streamlit, Docker, and Erlang C.

Code review modelled as an M/M/c queueing station: Erlang C, a Little's Law WIP cap, and an admission controller for agent-authored pull requests.

Queueing Models implemented in .NET

⚖️ Local-first System Design Capacity Simulator — queueing analytics (Erlang-C/M/M/c/K) + discrete-event simulation, SLO planning, zero dependencies | 本地优先的系统设计容量模拟器，排队论解析×离散事件仿真双引擎

Interval-level WFM forecasting exposing the aggregate trap: total staffing within ~2% of requirement, yet 53% of intervals understaffed. Erlang C, shrinkage modeling, FTE gap analysis in Python.

Schedule redistribution delivered +20.2% service level improvement vs +8.1% from headcount. Five WFM levers tested head to head — no new hires required.

These documents by Tawabiry exhibit the maturity, theoretical depth, and synthesis capabilities typically aimed at Graduate Level (MS/PhD) Applied Research or Senior Staff Engineering Design Docs at major tech firms (L6/L7 level).

[ARCHIVED] Consolidated into Vitalcheffe/over-engineer

Interval-level forecast variance, reforecasting, and staffing gap analysis for contact center WFM teams

A comprehensive staffing optimization tool using queue theory (M/M/c model) and stochastic modeling. Available as Flutter mobile app and web application.

A simulator about achieving contact center service level targets.

Browser-only contact center WFM workbench: interval volume forecasting (seasonal average, Holt-Winters, harmonic regression, ensemble), rolling-origin backtests, and Erlang A/C staffing with live what-if scenarios. No backend.