Stock math api

Search for the best way through the warehouse to collect different goods for further shipment to the client.

Application environment

following system environment variables are used for auth0 connection configuration.

APPLICATION_URL - URL of current instance, e.g. http://localhost:8080
APPLICATION_PORT - Port number backend shall listen on. Unless provided, port number from URL will be used, or default 8080
APPLICATION_BIND - IP address server shall listen on. Unless provided, 0.0.0.0 will be used
APPLICATION_ALLOWED_ORIGIN - Allowed origin for processing http requests. Unless provided, http://localhost:8000 will be used
APPLICATION_MACHINE_ID - Machine ID for current instance, used for snowflake generation (default: 1)
APPLICATION_NODE_ID - Node ID for current instance, used for snowflake generation (default: 1)

API Documentation

POST /calculate_optimal_path

request body:

geometry stock geometry how 2d array when i index how Y and j index how X
points is array of points (i,j) on which a person stands when he takes goods from the shelves.

responce body:

algorithm is algorithm type
distance_matrix_time how many time need for calculate graph (more details in "Solution" section)
traveling_salesman_time how many time need for calculate min path from graph (more details in "Solution" section)
distance how many steps need for getting goods from stock all shelves
path route min path

Example

POST /calculate_optimal_path
body
{
  "geometry": [
    ["W","W","W","W","W","W","W","W"],
    ["W","P","_","_","_","P","_","W"],
    ["W","W","W","_","W","W","W","W"],
    ["W","_","_","_","_","_","P","W"],
    ["W","W","W","_","W","W","W","W"],
    ["W","P","_","_","_","_","_","W"],
    ["W","W","W","_","W","W","W","W"],
    ["W","_","_","_","_","_","P","W"],
    ["W","S","_","_","_","_","_","_"],
    ["W","W","W","W","W","W","W","W"]
  ],
  "points": [
    [8, 1],
    [1, 1],
    [1, 5],
    [3, 6],
    [5, 1],
    [7, 6]
  ]
}
return:
{
    "algorithm": "simulated_annealing",
    "distance_matrix_time": "162.47µs",
    "traveling_salesman_time": "1.000004241s",
    "distance": 48.0,
    "path": [
        [8, 1],
        [1, 5],
        [1, 1],
        [3, 6],
        [5, 1],
        [7, 6],
        [8, 1]
    ]
}

Development

To start server use command: cargo run --bin chat

Open url: http://localhost:8080/

Docker

Build image

$ docker build --target runtime -t stock_math_api .

Run tests

$ docker build --progress=plain --target test -t chat-test .

Postmen examples

stock_math_api.postman_collection.json - located in repo

Solution

Calculate graph when set of nodes is 'Pi' and set of edges ('Pi', 'Pj') = min_path(geometry, Pi, Pj) min_path we calculate use bfs algorithm.
Solve traveling salesman problem for all nodes in calculated graph using Simulated_annealing algorithm.

Geometry example

W - wall or shelf P - point S - start point

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Debug OPTIONS

curl -i -X OPTIONS -H "Origin: http://127.0.0.1:3000" \
    -H 'Access-Control-Request-Method: POST' \
    -H 'Access-Control-Request-Headers: Content-Type' \
    "http://localhost:8080"

Next implementation

investigate Concorde TSP Solver
impement algorithms used concorde for TSP on rust

Sergo007 / stock_math_api