Ivan Rodin

Fuel distribution · trips from two depots →

Ivan Rodin

Operations research engineer

7+ years · Belgrade

About

Ivan Rodin

Operations research engineer in Belgrade with 7+ years of building optimization software for logistics, crew scheduling and industrial planning. I take a planning problem from the first formulation to a service in production, and I build OR Lens, an open-source plugin that lets AI agents inspect optimization models.

ivan@rodn.devLinkedInGitHubCV (PDF)

2026-now
Independent · Optimization engineer, contract work with a small team and my own clients
2023-26
ARHITEX · Mathematical optimization developer
2022-23
Rosterize · Mathematical optimization developer
2021-22
OZON · Operations research scientist
2018-21
SAS · Junior consultant
2015-21
Lomonosov Moscow State University · BSc and MSc, Applied Mathematics and Computer Science (Operations Research)

Work

15 projects · clients are not named · figures use synthetic data

01

Icebreaker convoys on the Northern Sea Route

When each ship sails alone and when it joins a convoy, hour by hour, as the ice changes from week to week.

Time-expanded MIP · HiGHS · in production · 3rd place, Leaders of Digital Transformation 2024

Convoys along an abstract Arctic route; icebreakers in red, standby positions as rings · synthetic data
02

Floor plans from an apartment mix

A target apartment mix turned into buildable floors: facades, lift-and-stair cores, shafts, wet zones and daylight rules.

Chain of MILPs · CPLEX · HiGHS · Gurobi

One generated floor; one apartment in red · synthetic data
03

Fuel distribution

How much fuel each filling station receives and when, then which tanker drives which trip, within tank capacities and station time windows.

Flow model → trip scheduling · CPLEX · in production

06:00-10:0009:00-13:0012:00-16:00
One planning day: tank farms, filling stations and tanker trucks; one truck’s trip and its time windows in red · synthetic data
04

Double round-robin tournaments

Sports timetables where every team meets every other twice, under capacity, break, separation and fairness rules.

A portfolio of MILP formulations · 3rd of 13 teams at ITC2021 · paper at PATAT 2021

11018second half mirrors the firstT1T2T3T4T5T6T7T8T9T10
Home ■ and away □ for ten teams; breaks, two in a row, in red · synthetic data
contactremote

Aircraft stand allocation

A day of arrivals and departures on 275 stands: jet bridges, buses, taxiing and wide-body neighbors.

MILP · CBC · 3rd place, Leaders of Digital 2021

Cash collection for 1,630 terminals

A deposit forecast for every terminal, then armored-car routes chosen day by day for three months.

N-BEATS · set-covering MIP · HiGHS · Leaders of Digital Transformation 2023

OT 1OT 2

Hospital timetabling

Admissions, operating theaters and nurse rosters as one problem, with ten minutes per instance.

MIP decomposition · local search · Gurobi · IHTC 2024

JanFebMarAprMayJunJulAugSepOctNovDecE01E02E03E04E05E06E07E08

A year of vacations

Cover the work first, then give out vacations and grant requests, in strict order of priority.

Lexicographic MILP · 1st place, Ramaximization 2021

materialssemi-finishedfinishedswitch

Multi-level MRP

How much to buy and how much to make at each stage and site, week by week, with lead times, minimum orders, stock targets and product changeovers.

Multi-period MILP · HiGHS · Gurobi

center 1center 2center 3

Weekly production plan for a food plant

A week of production across several production centers: stages of fixed length on shared lines, then warehouses that ship to customers, against sales and stock targets.

MILP · HiGHS · CPLEX · in production

suppliersplantsnational DCsregional DCscustomers

Warehouse and production network

Which plants and warehouses to open at each tier and how goods flow from suppliers to customers, at transport tariffs from a rate database. An AI agent helps the analysts interpret the results.

MILP · Pyomo · HiGHS · in production

week 1week 2week 3crew 1crew 2crew 3crew 4crew 5crew 6crew 7

Crew rostering and workforce scheduling

Air-crew rosters and retail shifts: coverage, qualifications, labor rules and preferences as hard and soft constraints.

MILP · CPLEX · Gurobi · HiGHS

Long-haul network for e-commerce

Routes and movement schedules for a long-haul transportation network, planned together under capacity and timing constraints.

MILP · Pyomo · CPLEX · in production

machine 1machine 2machine 3machine 4machine 5

Job-shop scheduling for an ERP

Operations of every order on shared machines, each order following its own route through the shop.

OR-Tools CP-SAT

Flatovo

A live rental search for Belgrade: listings from portals and Telegram, map search, photo deduplication and ranking by taste.

Next.js · FastAPI · PostGIS · pgvector · SigLIP

OR Lens explaining why a supply network model is infeasible, with the workbench beside the chat
Demo · Codex asks OR Lens why a supply network model will not solve

OR Lens

Debug optimization models with facts, not guesses.

A plugin for Claude Code and Codex. Ask about an LP or MPS file in chat: HiGHS extracts the conflict, an independent re-solve confirms it, and the workbench opens beside the chat.

Statuses, conflicts and objective values come from HiGHS and independent checks, never from the language model.

claude plugin marketplace add ivs-rodin/or-lens-plugin
claude plugin install or-lens@or-lens

github.com/ivs-rodin/or-lens-plugin · MIT · runs locally

stolp

Explains why an optimization model is infeasible.

A Python library for Pyomo models and LP or MPS files. It splits the model in halves, first by constraint groups and then inside them, until only the conflict is left, and says what to switch off. OR Lens will use it next.

pip install git+https://gitlab.com/tarasov.alexey/stolp.git@main

gitlab.com/tarasov.alexey/stolp · MIT · v0.2.1

groupsconstraintsbalancedemandstock_minshiftssupplycapacitysetupbatchswitch offdemand[3]stock_min[3]capacity[2]
Halves by groups, then inside each group · synthetic model

Publications

  1. PaperAccelerating sequential quadratic programming for inequality-constrained optimization near critical Lagrange multipliersA. F. Izmailov, I. S. Rodin. Advances in Systems Science and Applications 22(2), 2022, pp. 73-84
  2. AbstractAccelerating sequential quadratic programming near critical Lagrange multipliers (in Russian)A. F. Izmailov, I. S. Rodin. Tikhonov Readings 2021, abstracts, Lomonosov Moscow State University, p. 110
  3. PaperMILP based approaches for scheduling double round-robin tournamentsD. Sumin, I. Rodin. Proceedings of PATAT 2021, vol. II

ivan@rodn.dev