Solvers sketched by hand,
tuned to your operation✓

YI ALGORITHMS LLC turns messy operational constraints into clean, provable plans. We design optimization models, scheduling and routing engines, data pipelines, forecasts and live production solvers for teams that move people, freight, crews, robots and work together every day.

No generic tool. No black box that answers to nobody. We sit at the bench, draw the search tree, mark the dead branches in red, and circle the branch worth running.

Start an Analysis See the Six Workstreams

A brass stopwatch reads elapsed run; do we accept this branch or cut it?

Why a derivation bench beats a dashboard

Operations produce streams of choices. Which truck leaves which gate; which task a crew takes next; how many units a shift should build; where a patient slot goes; how much inventory a line should hold. A dashboard reports what happened. An algorithm derivation decides what should happen next before the clock runs out.

We write the model, test it against your true constraints, break it with your worst-case days, then wrap it in a reliable service your team can call thousands of times a day. Every piece is documented as an engineer would document a proof: assumptions stated, bounds derived, trade-offs marked.

The derivation begins with a question your floor actually hears. Do the morning gates clear by nine. Can the night shift hold without overtime. Which depots cover the wet zone when two trucks drop. Once the question is that precise, the model has a spine to build on, and the eraser stays busy only where the trade-offs genuinely fight each other.

9×

typical improvement in useful answer time at feasible margin

97%

of routed operations stay inside the service window we target

-31%

median cost drop across shipped production pilots we tune

Six fold steps on the solver bench

Each service is a sheet you open. Start anywhere; most operations begin where yours is stuck.

Optimization Model Design

step 01

A mathematical model is the single sheet of truth that binds your constraints and your goal. We translate queues, capacities, due dates, resource ceilings and service rules into a clean objective with controlled slack, then pick the exact solver class that fits: linear, integer, convex or constraint ordering. The model becomes readable, testable and safe to adjust when next week changes the rules. Bounds on run time come with the sheet, so your team knows before launch whether the answer will arrive in seconds or in a quiet overnight window.

Scheduling and Routing Algorithms

step 02

When work must land on a clock, we build schedulers that respect every hard rule and soften only what your business allows. Shift rosters, job shops, preventive maintenance windows, last-mile routes and multi-drop delivery all fit one family of decision problems we have tuned for real fleets and crews. Expect tight horizons, fast re-runs and answers that stay feasible.

Data Pipeline Engineering

step 03

A good model dies without good feed. We design pipelines that collect, clean, join and version your operational data so every solver call sees the same dependable picture. Reconciliation checks walk before the model runs; drift monitors warn when the incoming world changed more than the model expects. You keep ownership of the data; we keep the flow honest.

When a sink stops, the pipeline tells your team which upstream feed failed and why, instead of silently feeding a stale world into the optimizer. That early warning is worth more than a late detective hunt across three systems after the schedule already went out wrong.

Forecasting and Estimation Models

step 04

Planning needs the next number before the next event. We estimate demand, load, drive time, yield and failure likelihood from historical signals, choose seasonal baselines with care, and keep error bands honest so your planners never build confidence on a point guess. Forecast output plugs straight into the optimizer as its forward-looking demand layer.

Simulation and Scenario Testing

step 05

Before a plan meets the live floor, we run it against thousands of forged days. Monte Carlo roll-over events, delay trees, labour swings and spike demand compose into replay simulations that expose where a schedule cracks. Confidence intervals come from runs, not from optimism, and the red feasibility cross marks where a decision is truly not safe to take.

The output is a plain scoreboard a manager can read: how often the plan finished on time, how deep the worst overrun went and which single rule caused the most trouble. That page of honest numbers is what a floor trusts when it agrees to switch from the old habit to the derived plan.

Production Integration and Tuning

step 06

Deployment is the last fold of the sheet. We expose the solver behind clean endpoints, add retries and graceful fallbacks, monitor run time and solution quality, then tune parameters against live data once the real traffic arrives. When production changes, we re-derive, re-test and re-ship with the same rigour as the first build.

Run two ways: guess hard, or guide tight

Every everyday plan competes against these two search temperaments. We never ship the first one.

Random guessing

Brute force tries every combination in turn and keeps almost nothing. The path darts across the board with no sense of direction, re-exploring the same bad zone. With even fifty choices the search space explodes past what any clock can forgive, and the few feasible answers it finally touches arrive much too late to steer the day.

Lichen convergence

A guided search reads the objective at each step and leans toward branches that improve it, so the trace descends smoothly and bends toward the quiet lichen dot at the close. It still explores when it must, but it spends its seconds where the answer actually lives. The schedule lands feasible, on time, and within the window your floor truly needs.

Analysis window is open

YI ALGORITHMS LLC is taking on new model work for the coming quarter: routes, rosters, allocations and pipeline builds that need a careful derivation, not another dashboard. Send one problem note and we reply with a clear direction within the week.

Send a Problem Note