How to Implement Weighted Random Selection in Java?

Weighted Random Selection in Java

When selecting an item from a set, it's often desirable to assign different probabilities to different items. This method is known as weighted random selection.

Consider the following scenario where you have a collection of items with associated weights:

Item	Weight
Sword of Misery	10
Shield of Happy	5
Potion of Dying	6
Triple-Edged Sword	1

In this case, the weight represents the likelihood of selecting that item. For example, you are 10 times more likely to obtain the Sword of Misery than the Triple-Edged Sword.

To implement weighted random selection in Java, we can employ a NavigableMap:

import java.util.NavigableMap;
import java.util.Random;
import java.util.TreeMap;

public class RandomCollection<E> {
    private final NavigableMap<Double, E> map = new TreeMap<>();
    private final Random random;
    private double total = 0;

    public RandomCollection() {
        this(new Random());
    }

    public RandomCollection(Random random) {
        this.random = random;
    }

    public RandomCollection<E> add(double weight, E result) {
        if (weight <= 0) return this;
        total += weight;
        map.put(total, result);
        return this;
    }

    public E next() {
        double value = random.nextDouble() * total;
        return map.higherEntry(value).getValue();
    }
}

Usage:

RandomCollection<String> rc = new RandomCollection<>()
        .add(40, "dog").add(35, "cat").add(25, "horse");

for (int i = 0; i < 10; i++) {
    System.out.println(rc.next());
}

This code demonstrates how to add items with specific weights to the collection and then select random items based on their assigned probabilities.

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