feat: add UnboundedKnapsack algorithm #1428

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		* [RodCutting](Dynamic-Programming/RodCutting.js)
		* [Shuf](Dynamic-Programming/Shuf.js)
		* [SieveOfEratosthenes](Dynamic-Programming/SieveOfEratosthenes.js)
	* [UnboundedKnapsack](Dynamic-Programming/UnboundedKnapsack.js)
		* Sliding-Window
		* [HouseRobber](Dynamic-Programming/Sliding-Window/HouseRobber.js)
		* [LongestSubstringWithoutRepeatingCharacters](Dynamic-Programming/Sliding-Window/LongestSubstringWithoutRepeatingCharacters.js)
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36 changes: 36 additions & 0 deletions Dynamic-Programming/UnboundedKnapsack.js

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	/**
	* @function unboundedKnapsack
	* @description Solve the Unbounded Knapsack problem using Dynamic Programming.
	* @param {number[]} weights - An array of item weights.
	* @param {number[]} values - An array of item values.
	* @param {number} capacity - The maximum capacity of the knapsack.
	* @return {number} The maximum value that can be obtained.
	* @see [UnboundedKnapsack](https://en.wikipedia.org/wiki/Knapsack_problem#Unbounded_knapsack_problem)
	*/

	function unboundedKnapsack(weights, values, capacity) {
	const n = weights.length;

	// Create a DP array to store the maximum value for each possible knapsack capacity.
	const dp = new Array(capacity + 1).fill(0);

	// Loop through each possible knapsack capacity from 0 to the maximum capacity.
	for (let w = 0; w <= capacity; w++) {
	// Loop through each item in the given items.
	for (let i = 0; i < n; i++) {
	// Check if the weight of the current item is less than or equal to the current knapsack capacity.
	if (weights[i] <= w) {
	// Update the DP array with the maximum value between not taking the current item
	// and taking the current item and adding its value.
	dp[w] = Math.max(dp[w], dp[w - weights[i]] + values[i]);
	}
	}
	}

	// The final element of the DP array stores the maximum value that can be obtained with
	// the given knapsack capacity.
	return dp[capacity];
	}

	export { unboundedKnapsack };

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