Add CLAUDE.md and README.md documentation
Documents the GA-based seating solver's architecture, config file chain, and setup/usage for both AI assistants and human contributors. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
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# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project overview
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`platz` (German: "Sitzplatzverteilung" / seating arrangement) is a genetic-algorithm-based
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solver that assigns people to tables ("Tische") for an event, given group memberships, table
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sizes/neighbor relationships, and a penalty scheme. It reads an XML order/guest list and INI
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table layout, runs a small custom GA framework to search for a good seating, and writes the
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result to text/CSV output files.
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**This is Python 2 code** (print statements, `ConfigParser`, `sets.Set`, `UserList`,
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`string.split`, old-style `raise Exception, "msg"`, `xrange`, `dict.has_key`,
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`dict.iteritems`). It will not run under Python 3 without a 2to3-style port. There is no
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`requirements.txt`, build system, test suite, or linter configured in this repo — a Python 2
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interpreter with only the standard library is sufficient to run it.
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## Running the program
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Entry point is `libs/platz.py`, invoked via the wrapper scripts in `bin/`, which set up
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environment variables and `PYTHONPATH` before calling it — the scripts never take a script
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argument, they just launch `platz.py`:
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- `bin/run` (bash, for Linux/macOS) — hardcodes `PLATZ=/Users/sm/develop/python/platz`
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- `bin/run.bat` (Windows) — hardcodes `PLATZ=h:\develop\python\platz` and a Python 2.4 interpreter path
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Both scripts set `PLATZ_CFG`, `PLATZ_LIBS`, `PLATZ_WORK` and add `PLATZ_LIBS` to
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`PYTHONPATH`, then run `python $PLATZ_LIBS/platz.py`. **The hardcoded paths at the top of
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these scripts must be edited to match wherever this repo is actually checked out** before
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they will work.
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Configuration is driven by `cfg/platz.cfg`, which points (via `$PLATZ_CFG`/`$PLATZ_WORK`
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env-var expansion) to:
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- `cfg/zyklus.cfg` — defines the GA run schedule ("Zyklus"): a sequence of actions
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(`e`=erzeugen/create, `s`=selektieren/select-best, `S`=random-select, `m`=mutieren/mutate,
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`j`=behalten/keep parents, `z`=neue Generation/advance generation) each with a count.
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- `cfg/strafen.cfg` — the penalty ("Strafpunkte") table: cost of splitting a group across
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tables (by group size and number of splits), cost of a lone person, and per-table
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under-utilization penalties.
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- A per-run working directory under `work/<name>/` (e.g. `work/test1/`, `work/test2/`)
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containing:
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- `tische.ini` — table definitions: id, `Nummer`, `Hof` (venue/court), `Plaetze` (seats),
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`Nachbarliste` (neighbor table ids), `Koordinaten`.
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- `bestellung.xml` — the guest order: `<Gruppe>` blocks containing `<Person>` (with
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`Vorname`/`Nachname`/optional `Titel`) and an `<Anzahl>` (reservation count per person
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template — this expands into that many identical bookings), plus optional `<Tisch>` to
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pin a VIP group to a specific table.
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- Output: `TischePersonen.txt` (table → seated people) and `PersonenTische.csv`
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(person → table, sorted).
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## Architecture
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Two library modules under `libs/`, imported via `PYTHONPATH=$PLATZ_LIBS`:
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### `ga.py` — generic genetic-algorithm scaffolding
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Domain-agnostic and reusable in principle:
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- `Loesung` ("Solution") — base class for anything bred/mutated/selected by the GA. Meant to
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be subclassed; `Sitzplatzverteilung` in `Strukturdaten.py` is the concrete solution type
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used here.
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- `Zyklus` ("Cycle") — parses `Abfolge`/`Anzahl` strings (from `zyklus.cfg`) into the ordered
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list of GA actions and their counts for one run.
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- `Farm` — owns the population (`Pool`/`PoolNeu`), and executes a `Zyklus` action-by-action
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against instances of a given solution class (passed as `Klasse` plus its constructor
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args/kwargs). `Bester()` returns the fittest (`max()`) solution found; solutions are ordered
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via `__cmp__` on `self.value`.
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### `Strukturdaten.py` — domain model for this specific seating problem
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- `Person`, `Gruppe` (group — a `Set` of people, splittable via `teilen()`), `Tisch` (table —
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a `Gruppe` subclass with a seat capacity and neighbor-table ids).
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- Container/index classes: `Personen`, `Gruppen`, `Tische`, and `Plaetze` ("Seats") which
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indexes tables by how many free seats they currently have, to answer "give me a table with
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at least N free seats" or "give me two neighboring tables that together fit two groups of
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given sizes" efficiently during placement/mutation.
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- `Strafliste` ("Penalty list") — loads `strafen.cfg` and computes penalty points for: splitting
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a group (`gibPunkte('Trennung', ...)`, recursing to smaller group sizes if no exact rule is
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configured), a person sitting with no group-mate at their table (`'allein'`), a person having
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no group-mate at a *neighboring* table (`'nichtNachbar'`), and poor seat utilization at a
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table (`'Tischbesetzung'`).
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- `Sitzplatzverteilung` ("Seating arrangement") — the actual `Loesung` subclass bred by the GA.
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Constructor seats VIPs first at pinned tables, then randomly seats groups either
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largest-first or smallest-first (coin flip), splitting a group across two neighboring tables
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when no single table has enough free seats, recursively splitting further if needed, then
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calls `bewerten()` to score the arrangement per `Strafliste`. `mutieren()` picks the
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worst-scoring groups (`SchlechteGruppenTopX`), evicts them, and reseats them, hoping for a
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better score. `speichern()` writes the two output files.
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- `XMLConfig` — parses `bestellung.xml` into `Personen`/`Gruppen`/VIP-group/VIP-seat-map,
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expanding each `<Person>` template by its sibling `<Anzahl>` into that many individual
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bookings, and treating any `<Gruppe>` containing a `<Tisch>` tag as a VIP group pinned to
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that table rather than going through normal GA placement.
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### Data flow through `platz.py` (`__main__`)
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1. Read `platz.cfg` to locate the other config/data files (env-var expansion via
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`os.path.expandvars`).
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2. Load `Zyklus` (GA schedule), `Strafliste` (penalties), `Tische` (table layout).
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3. Load `bestellung.xml` via `XMLConfig` → people, groups, VIP group, VIP seat map.
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4. Build a `Farm(Zyklus, Sitzplatzverteilung, Tische=..., Gruppen=..., Strafen=...,
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VIPListe=..., VIPs=...)`, which runs the whole GA cycle in its constructor.
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5. Take `Farm.Bester()` and call `.speichern(...)` to write the output files.
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Both `libs/platz.py` and `libs/Strukturdaten.py` also have self-test code under
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`if __name__ == '__main__':` that exercises the classes directly with hardcoded sample data —
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useful as a reference for how the classes are meant to be constructed and used.
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# platz
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A genetic-algorithm-based solver that assigns people to tables ("Tische") for an event,
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given group memberships, table sizes/neighbor relationships, and a configurable penalty
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scheme. It reads a guest list (XML) and a table layout (INI), searches for a good seating
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using a small custom GA framework, and writes the result to text/CSV output files.
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**This is Python 2 code** (print statements, `ConfigParser`, `sets.Set`, `UserList`,
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`string.split`, old-style `raise Exception, "msg"`, `xrange`, `dict.has_key`,
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`dict.iteritems`). It needs a Python 2 interpreter; there are no third-party dependencies
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(standard library only).
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## Project structure
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```
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platz/
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├── bin/ # launcher scripts (bash + Windows batch)
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├── cfg/ # GA cycle definition and penalty scheme
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├── libs/ # the two Python modules (ga.py, Strukturdaten.py, platz.py)
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└── work/ # per-run input (table layout, guest list) and output
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├── test1/
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└── test2/
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```
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- `libs/platz.py` — entry point; wires together config, input data, and the GA run.
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- `libs/ga.py` — generic genetic-algorithm scaffolding (`Loesung`, `Zyklus`, `Farm`).
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- `libs/Strukturdaten.py` — domain model for the seating problem (`Person`, `Gruppe`,
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`Tisch`, `Strafliste`, `Sitzplatzverteilung`, `XMLConfig`).
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## Setup
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1. Install a Python 2 interpreter (2.4+; no `pip install` needed, standard library only).
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2. Edit the hardcoded paths at the top of the launcher script for your platform:
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- `bin/run` (bash): `PLATZ=/Users/sm/develop/python/platz`
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- `bin/run.bat` (Windows): `PLATZ=h:\develop\python\platz` and `PYTHONSHELL=l:\tools\i486_nt\python24`
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Point `PLATZ` at wherever you checked out this repository.
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## Running
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From a shell:
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```bash
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# Linux/macOS
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source bin/run
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```
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```bat
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:: Windows
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bin\run.bat
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```
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The launcher sets `PLATZ_CFG`, `PLATZ_LIBS`, `PLATZ_WORK`, adds `PLATZ_LIBS` to
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`PYTHONPATH`, and runs `libs/platz.py`.
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### Configuring a run
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`cfg/platz.cfg` selects which cycle/penalty config and which working directory
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(`work/<name>/`) to use for a given run:
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```ini
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[Config]
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Zyklusdatei=$PLATZ_CFG/zyklus.cfg
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Zyklusart=Easy
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Strafendatei=$PLATZ_CFG/strafen.cfg
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Tischedatei=$PLATZ_WORK/test1/tische.ini
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XMLdatei_Bestellung=$PLATZ_WORK/test1/bestellung.xml
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AusgabeTischePersonen=$PLATZ_WORK/test1/TischePersonen.txt
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AusgabePersonTisch=$PLATZ_WORK/test1/PersonenTische.csv
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```
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To run against a different dataset, point the `Tischedatei`/`XMLdatei_Bestellung`/output
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entries at another `work/<name>/` folder, or add a new one following the same layout:
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- `tische.ini` — one section per table: `Nummer`, `Hof` (venue/court), `Plaetze` (seat
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count), `Nachbarliste` (neighboring table ids), `Koordinaten`.
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- `bestellung.xml` — `<Gruppe>` blocks, each with a `<Person>` template
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(`Vorname`/`Nachname`/optional `Titel`) and an `<Anzahl>` (how many bookings to expand
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that template into). A `<Gruppe>` containing a `<Tisch>` tag is treated as a VIP group
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pinned to that table instead of being placed by the GA.
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`cfg/zyklus.cfg` defines the GA run schedule ("Zyklus") as an `Abfolge` (sequence of
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actions) and matching `Anzahl` (counts): `e` create, `s` select best, `S` select randomly,
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`m` mutate, `j` keep parents, `z` advance generation.
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`cfg/strafen.cfg` defines the penalty scheme: cost of splitting a group across tables (by
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group size and number of splits), cost of a person sitting alone or without a group-mate at
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a neighboring table, and per-table seat-utilization penalties.
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### Output
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A run writes two files into the configured working directory:
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- `TischePersonen.txt` — table → seated people, with venue/table/seat numbers.
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- `PersonenTische.csv` — person → table, sorted alphabetically by name.
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## Further details
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See `CLAUDE.md` for a deeper architectural walkthrough of the GA framework and domain
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model, intended for AI coding assistants but equally useful for human contributors.
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