SOT II 2026 · Production and distribution optimization

Solved cases

From textbook example to real network.

Three models solved with SOT II 2026 and a free solver on an ordinary computer. The figures are the program's actual output, not estimates.

Hover over or tap a route to see the tonnes.■ plant

Starting point

3,264.7transport cost

—vs. starting point

Example from the book Optimización del transporte (in Spanish). All three scenarios reproduce exactly the optimum of the original 1998 program.

	Book example	Real 5-product network (12 months)	Scale test
Network	4 origins, 10 destinations	18 plants and warehouses, 57 aggregated customer locations	8 plants, 35 warehouses, 1,457 customers
Products	1	5 products	5
Horizon	1 period	12-month season, with stock carried between months	1 period
Model size	54 variables, 14 constraints	75,105 variables, 5,247 constraints	27,100 variables, 7,500 constraints
Time to optimum, today	0.1 s	3.8 s	13.9 s
Same model in 1998	—	14 min 00 s	21 min 52 s
What it shows	Exact fidelity to the original system	A real industrial problem, solved in seconds	Ample headroom for very large networks

The real network is anonymized: no company, product or customer names, and no costs. The scale test is the book's REAL model, a synthetic case designed to measure capacity. Current times use the free HiGHS solver and include model building. 1998 times are from table E.1 of the book (90 MHz Pentium), for models of identical size: 75,105 and 27,100 variables.

The real network, month by month

Two different calendars: production and consumption.

In the real agricultural network, production is concentrated in two seasons, and demand is seasonal too, but on a different calendar: it rises in summer and autumn and drops in December, February and August. In a single calculation, SOT II 2026 decides how much to produce and pack, how much to store and in which warehouse, and which route serves each month, matching both calendars at minimum cost.

—thousand t produced in the year

—thousand t delivered to customers

—month of peak stock

Optimal solution computed with SOT II 2026: 18 plants and warehouses, 57 aggregated customer locations, 12-month season (October to September). Volumes in thousand tonnes. Anonymized data.

Ask the results

Talk to the optimal solution.

Copy a prompt that already contains the anonymized results of the real network, paste it into Claude, ChatGPT or the assistant you use, and ask anything: why stock builds up in a given month, what role each site plays, or what would need recalculating after a change.

Open Claude Open ChatGPT

Or start with a specific question; it is copied together with the prompt:

See the full prompt

Act as a senior operations and supply chain analyst. You are going to analyze the optimal solution that SOT II 2026 computed for the real network of a large Spanish agricultural company. The data is anonymized.

MODEL CONTEXT
- 18 plants and warehouses (17 active in the solution), 57 aggregated customer locations, 5 products and a 12-month season, October to September.
- Linear programming model with 5,247 constraints and 75,105 variables. SOT II 2026 reaches the optimum in about 4 seconds with a free solver; the same model took 14 minutes in 1998.
- The model decides production, packing, stock and transport simultaneously, minimizing the total cost of the network.
- Product 1 is the base product; products 2 to 4 are formats packed from it, so total production counts only the base product. Product 5 is an intermediate with no demand of its own and is not included.
- Volumes in thousand tonnes (kt). No costs or real names are included.

DATA 1. Monthly series
SERIES;Oct;Nov;Dec;Jan;Feb;Mar;Apr;May;Jun;Jul;Aug;Sep
Total · production and packing;77.1;112.3;126.9;58.8;7.2;7.0;7.2;7.2;87.2;100.2;67.0;7.2
Total · deliveries;57.2;59.0;42.6;55.8;45.6;49.0;48.4;48.4;59.9;58.6;45.3;59.5
Total · end-of-month stock;205.9;259.2;343.5;345.1;293.4;245.2;201.9;160.4;187.8;229.3;251.0;198.7
Product 1 · production and packing;77.1;112.3;112.3;29.4;33.9;19.5;11.5;7.7;87.2;100.2;41.0;7.2
Product 1 · deliveries;19.0;20.2;17.9;21.4;21.9;21.0;22.7;21.7;24.0;22.8;16.5;24.6
Product 1 · end-of-month stock;88.8;139.9;191.4;173.6;162.8;144.2;118.2;97.8;123.6;156.9;164.5;128.4
Product 2 · production and packing;31.1;20.1;18.9;9.0;0.1;0.5;0.0;0.0;18.3;26.4;5.5;11.4
Product 2 · deliveries;22.7;22.5;9.4;18.7;9.8;11.1;8.9;9.9;20.6;20.6;15.4;18.3
Product 2 · end-of-month stock;96.6;94.2;103.7;94.0;84.3;73.7;64.9;55.0;52.7;58.5;48.5;41.7
Product 3 · production and packing;3.9;3.5;5.5;3.6;1.5;1.7;2.6;1.2;3.8;2.8;2.8;1.0
Product 3 · deliveries;3.6;3.6;3.6;3.7;3.7;3.7;3.7;3.7;3.1;3.1;3.1;3.1
Product 3 · end-of-month stock;9.0;8.8;10.6;10.5;8.3;6.3;5.2;2.7;3.4;3.2;2.9;0.8
Product 4 · production and packing;19.2;17.5;18.6;12.0;7.8;8.7;10.0;5.0;15.3;14.8;8.5;6.3
Product 4 · deliveries;11.8;12.7;11.7;12.1;10.2;13.1;13.1;13.2;12.2;12.1;10.3;13.6
Product 4 · end-of-month stock;11.5;16.3;23.2;23.1;20.7;16.2;13.1;5.0;8.1;10.8;9.0;1.7

DATA 2. Sites, ordered by volume
SITE;annual production (kt);annual shipments (kt);months with production
Site 01;92.6;68.8;3
Site 02;74.8;78.0;4
Site 03;75.0;68.6;4
Site 04;63.7;74.3;3
Site 05;55.7;60.2;8
Site 06;55.2;56.5;4
Site 07;41.2;46.0;4
Site 08;53.5;26.7;3
Site 09;53.5;24.3;3
Site 10;41.2;36.4;4
Site 11;34.3;35.9;4
Site 12;24.6;22.1;3
Site 13;0.0;18.0;0
Site 14;0.0;14.7;0
Site 15;0.0;11.7;0
Site 16;0.0;5.4;0
Site 17;0.0;0.1;0

DATA 3. Deliveries by region and month (kt; regions of Spain, plus exports)
REGION;Oct;Nov;Dec;Jan;Feb;Mar;Apr;May;Jun;Jul;Aug;Sep;total
Catalonia;11.9;12.7;11.3;12.8;12.7;13.0;13.2;13.0;13.5;13.1;10.1;13.5;150.8
Madrid;6.9;7.3;6.5;7.4;7.2;7.5;7.7;7.6;7.8;7.5;5.9;7.9;87.2
Export;12.4;11.2;0.0;8.5;0.0;0.0;0.0;0.0;11.4;11.3;7.4;11.3;73.5
Andalusia;5.0;5.4;4.8;5.3;4.9;5.5;5.4;5.4;5.3;5.2;4.3;5.3;61.8
Valencian Community;4.3;4.6;4.1;4.5;4.3;4.7;4.6;4.6;4.6;4.5;3.6;4.5;52.9
Galicia;2.7;2.9;2.6;2.9;2.7;3.0;3.0;3.0;3.0;2.9;2.3;3.1;34.0
Castile and León;2.0;2.2;1.9;2.1;1.9;2.2;2.1;2.1;2.1;2.0;1.7;2.0;24.2
Cantabria;1.9;2.0;1.8;2.0;1.9;2.0;2.0;2.0;2.0;1.9;1.6;1.9;22.9
Basque Country;1.8;1.9;1.7;1.9;1.8;2.0;2.0;2.0;2.0;2.0;1.6;2.1;22.9
Murcia;1.7;1.8;1.7;1.7;1.7;1.8;1.7;1.8;1.6;1.6;1.4;1.5;20.0
Castile-La Mancha;1.5;1.7;1.4;1.6;1.6;1.7;1.6;1.6;1.6;1.6;1.3;1.5;18.9
Aragon;1.4;1.5;1.4;1.5;1.4;1.6;1.5;1.5;1.5;1.5;1.2;1.4;17.4
Extremadura;1.1;1.2;1.1;1.1;1.0;1.2;1.1;1.2;1.1;1.1;0.9;1.0;13.3
Asturias;1.1;1.2;1.0;1.1;1.0;1.2;1.1;1.1;1.1;1.1;0.9;1.0;12.8
Balearic Islands;0.6;0.7;0.6;0.6;0.6;0.7;0.6;0.6;0.6;0.6;0.5;0.5;7.2
La Rioja;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.3;0.4;4.8
Navarra;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.4;0.3;0.4;4.6

HOW I WANT YOU TO WORK
1. Start with a five-line executive summary for an operations director.
2. Explain how the solution matches the production calendar with the demand calendar: when stock builds up, when it is drawn down and what role the warehouses play.
3. Point out the three most relevant findings, with specific figures taken from the data.
4. Then answer my questions using only this data. If something cannot be known from it, say so. If a question requires recomputing (closing a site, changing demand or a cost), do not invent the result: explain which scenario should be run in SOT II 2026 and what you would expect to see.
Answer in English.

The AI reasons about the solution already computed; it does not recompute it. To evaluate a new scenario with a guaranteed optimum, that scenario is solved in SOT II 2026.

What it solves

One global optimum, not piecemeal decisions.

Planning production and distribution in a company with several plants, many products and strong seasonality is slow, and replanning when a cost, a capacity or demand changes is slower still. Decisions are usually made with the best intuition available, not with the best possible solution.

SOT II 2026 formulates the whole problem as a linear programming model and solves it in one pass: which market each plant serves, how much it produces and stores in each period, and by which route, all at minimum total cost. The result is not just a good solution; it is the model's optimum, and it is defensible.

How it works

From your data to the decision, in four steps.

One

Model

Describe your network (plants, products, periods, costs, capacities) in the SOT language.

Two

Build

SOT II 2026 generates the linear programming model: thousands of equations and variables.

Three

Optimize

The solver finds the minimum-cost plan that satisfies every constraint.

Four

Report

Results in Excel and an interactive dashboard, ready to decide and explain.

Why SOT II 2026

Proven, modern and under your control.

Rewritten for 2026

28 years of validated logic, now in modern, maintainable Python (Pyomo). A free solver by default; Xpress or Gurobi when you need them, without touching the model.

On your own computer

It runs on your computer, with no cloud platform and no annual subscription. Your data never leaves the company.

Interface and reports

Local web application, executive summary, full detail and an interactive results dashboard.

Scenario analysis

Evaluate closures, expansions or changes in demand and cost before they happen. Replan in minutes, not days.

Who it is for

Any network with plants, warehouses and customers.

SOT II 2026 is not built for a single industry: it works wherever you must decide what to produce, where to store it and how to get it to each customer. Some examples:

Food and beverages

Which plant packs each format and how to supply retail in peak season without running out of stock.

Agribusiness

Harvest seasons concentrated in a few months, intermediate storage and sales spread across the year.

Meat and processed foods

Perishable product with short lead times between plant, cold store and customer.

Cement, ceramics and building materials

Heavy product where freight cost decides which plant serves each market.

Chemicals and fertilizers

Seasonal demand, bulk transport and conversion of intermediate products into finished goods.

Energy and fuels

Refineries, terminals and depots supplied by ship, pipeline or truck.

Paper, pulp and wood

Raw material scattered across a region, collected and hauled in bulk to several mills.

Distribution and logistics

Regional warehouses, store replenishment and transfers between sites.

The horizon fits the decision.

You define the periods: days or weeks for operations, months for the season or the annual budget, years for investment, expansion or closure decisions. The same model links the periods through the stock carried from one to the next.

How we work

Success-based, no fixed fee.

No savings, no invoice.

Free diagnostic.I spend a day reviewing your problem and tell you frankly whether SOT II 2026 adds value. No cost, no commitment.
Success-based fee.We analyze your data, evaluate an improvement for one year, and my fee is a percentage of that first year's savings.
Then, tailored to you.A software licence for your own computers and, if you wish, an ongoing modelling service.

About the author

Enrique Parra Iglesias

Telecommunications Engineer (Ingeniero Superior de Telecomunicación, a master's-level degree) and PhD in Economics. Associate Professor (Profesor Titular) at the University of Alcalá, Spain, where he has taught mathematics, operations research and energy economics.

Thirty-five years at the CEPSA group (now Moeve), from operations research analyst and project lead to CFO of Refining, with twenty years of responsibility for budgeting and management control and seats on several boards of directors. He has developed more than twenty software systems for management control and operations research.

Optimización del transporte. Modelos resueltos con SOT II.
Enrique Parra Iglesias. Díaz de Santos, 1999. ISBN 84-7978-384-2. In Spanish: “Transport optimization: models solved with SOT II”.

The book that published the SOT II mathematical model and the cases that SOT II 2026 now reproduces exactly.

View the book on Amazon (Spain)

Recent Springer publications

Utilizing Large Language Models for Building and Solving Production and Transportation Optimization ModelsLecture Notes on Data Engineering and Communications Technologies, Springer, 2025
A Real Case on Making Strategic Logistics Decisions with Production and Inventory Optimization ModelsAIRO Springer Series, 2019
A Software for Production-Transportation Optimization Models BuildingAIRO Springer Series, 2018

For the full track record, I am happy to send my CV.

Request the CV

The best plan for your whole network, calculated.

lower logistics cost, audited.