Распределение всего элемента по соотношению

Используйте двойную математику, округлите в меньшую сторону, а затем случайным образом раздайте оставшиеся фрукты, взвешенные на основе соотношения. Обратите внимание: вы можете сделать это намного менее уродливым с помощью объектной ориентации и циклов, но это только начало.

public void distribute(int apple, int pear, int grape) {
    double total = apple + pear + grape;
    double appleRatio = apple/total;
    double pearRatio = pear/total;
    double grapeRatio = grape/total;

    // apple worker
    int appleWorkerApple = (int) (appleRatio*apple);
    int appleWorkerPear = (int) (appleRatio*pear);
    int appleWorkerGrape = (int) (appleRatio*grape);

    // pear worker
    int pearWorkerApple = (int) (pearRatio*apple);
    int pearWorkerPear = (int) (pearRatio*pear);
    int pearWorkerGrape = (int) (pearRatio*grape);

    // grape worker
    int grapeWorkerApple = (int) (grapeRatio*apple);
    int grapeWorkerPear = (int) (grapeRatio*pear);
    int grapeWorkerGrape = (int) (grapeRatio*grape);

    int appleRemain = apple - appleWorkerApple - pearWorkerApple - grapeWorkerApple;
    int pearRemain = pear - appleWorkerApple - pearWorkerApple - grapeWorkerApple;
    int grapeRemain = grape - appleWorkerApple - pearWorkerApple - grapeWorkerApple;

    Random r = new Random();
    while(appleRemain > 0 && pearRemain > 0 && grapeRemain > 0) {
        double target = r.nextDouble();
        switch(r.nextInt(3)) {
        case 0:
            if(appleRemain > 0) {
                appleRemain--
                if(target < appleRatio)
                    appleWorkerApple++;
                else if (target < appleRatio + grapeRatio)
                    pearWorkerApple++;
                else
                    grapeWorkerApple++;
            }
            break;
        case 1:
            if(grapeRemain > 0)
            // etc.
        }
    }
}

Это не особенно полезно, потому что я слишком много использовал Numpy, но я поделюсь, так как это актуально

import numpy
import random

# apple, bannana, grapes, guava, melon, pear
fruits = numpy.array([100, 150, 175, 200, 230, 247])

# Bill, Bob, Dan, Fred, Joe
ratios = numpy.array([21, 7, 32, 13, 27])

# Original fruit amount for each worker: 0
worker_fruits = numpy.zeros((5, 6), dtype=int)
worker_lucky  = numpy.zeros((5, 6), dtype=float)

# For each worker with his ratio
for worker, lucky, ratio in zip(worker_fruits, worker_lucky, ratios):
    # Give him fruits, storing partials as weighting
    to_give = (ratio * fruits) / 100
    lucky  += to_give % 1
    worker += to_give

# Calculate how much we have left over
spares = fruits - worker_fruits.sum(axis=0)

# Share it out in a weighted distribution
for fruit, lucky, numspare in zip(worker_fruits.transpose(), worker_lucky.transpose(), spares):
    if numspare:
        indexes = numpy.arange(len(fruit))
        add_to = numpy.random.choice(indexes, replace=False, size=numspare, p=lucky/numspare)
        fruit[add_to] += 1

# Our results!
worker_fruits
#>>> array([[21, 31, 36, 42, 49, 51],
#>>>        [ 7, 11, 12, 14, 16, 18],
#>>>        [32, 48, 56, 64, 74, 79],
#>>>        [13, 19, 23, 26, 29, 32],
#>>>        [27, 41, 48, 54, 62, 67]])

# Proof it's perfectly shared
fruits - worker_fruits.sum(axis=0)
#>>> array([0, 0, 0, 0, 0, 0])