tools/picking.py

import pandas as pd
import matplotlib.pyplot as plt
from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp


def optimize_picking_route(df: pd.DataFrame):
    df = df.copy()

    # Convert to points
    coords = df[["Aisle", "Rack"]].values.tolist()

    # Distance matrix (Manhattan)
    size = len(coords)
    dist = [[abs(a1 - a2) + abs(r1 - r2)
             for (a2, r2) in coords] for (a1, r1) in coords]

    # Solver
    manager = pywrapcp.RoutingIndexManager(size, 1, 0)
    routing = pywrapcp.RoutingModel(manager)

    def dist_callback(i, j):
        return dist[manager.IndexToNode(i)][manager.IndexToNode(j)]

    transit_idx = routing.RegisterTransitCallback(dist_callback)
    routing.SetArcCostEvaluatorOfAllVehicles(transit_idx)

    params = pywrapcp.DefaultRoutingSearchParameters()
    params.first_solution_strategy = routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC

    solution = routing.SolveWithParameters(params)

    order = []
    idx = routing.Start(0)
    while not routing.IsEnd(idx):
        order.append(manager.IndexToNode(idx))
        idx = solution.Value(routing.NextVar(idx))

    ordered_df = df.iloc[order]

    # Plot
    plt.figure(figsize=(5, 5))
    plt.plot(ordered_df["Aisle"], ordered_df["Rack"], marker="o")
    plt.title("Optimized Picking Route")
    plt.xlabel("Aisle")
    plt.ylabel("Rack")
    img_path = "/tmp/route_plot.png"
    plt.savefig(img_path)
    plt.close()

    return img_path, ordered_df