Below is the implementation of the shopping offers:
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140/** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Recursion with Memoization approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffers(price, special, needs) { // Memoization map to store results of subproblems const memo = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function dfs(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (memo.has(key)) { return memo.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + dfs(newNeeds)); } } // Memoize and return the result memo.set(key, result); return result; } return dfs(needs);} /** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Dynamic Programming approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffersDP(price, special, needs) { // DP map to store results of subproblems const dp = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function solve(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (dp.has(key)) { return dp.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + solve(newNeeds)); } } // Store the result in the DP table dp.set(key, result); return result; } return solve(needs);} // Test casesconsole.log(shoppingOffers([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0 console.log(shoppingOffersDP([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0
Let's break down the implementation:
Implement the shopping offers solution in different programming languages.
Below is the implementation of the shopping offers in different programming languages. Select a language tab to view the corresponding code.
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140/** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Recursion with Memoization approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffers(price, special, needs) { // Memoization map to store results of subproblems const memo = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function dfs(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (memo.has(key)) { return memo.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + dfs(newNeeds)); } } // Memoize and return the result memo.set(key, result); return result; } return dfs(needs);} /** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Dynamic Programming approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffersDP(price, special, needs) { // DP map to store results of subproblems const dp = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function solve(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (dp.has(key)) { return dp.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + solve(newNeeds)); } } // Store the result in the DP table dp.set(key, result); return result; } return solve(needs);} // Test casesconsole.log(shoppingOffers([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0 console.log(shoppingOffersDP([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0
Understand that we need to find the minimum cost to buy exactly the needed items, using special offers optimally.
Use recursion to explore all possible combinations of special offers and regular purchases, with memoization to avoid redundant calculations.
For each special offer, check if it's valid (i.e., it doesn't exceed our needs for any item).
If an offer is valid, update the needs by subtracting the items in the offer, and recursively solve the problem for the updated needs.
Also consider the option of not using any special offer and buying all items at their regular prices.
Modify the code to implement an alternative approach and test it with the same examples.
Implement a function that solves the shopping offers problem using a different approach than shown above.
Handle the case where there are no needed items (return 0).
Handle the case where there are no special offers (buy all items at their regular prices).
Handle the case where using special offers is not optimal (buy all items at their regular prices).
Below is the implementation of the shopping offers:
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140/** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Recursion with Memoization approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffers(price, special, needs) { // Memoization map to store results of subproblems const memo = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function dfs(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (memo.has(key)) { return memo.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + dfs(newNeeds)); } } // Memoize and return the result memo.set(key, result); return result; } return dfs(needs);} /** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Dynamic Programming approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffersDP(price, special, needs) { // DP map to store results of subproblems const dp = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function solve(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (dp.has(key)) { return dp.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + solve(newNeeds)); } } // Store the result in the DP table dp.set(key, result); return result; } return solve(needs);} // Test casesconsole.log(shoppingOffers([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0 console.log(shoppingOffersDP([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0
Let's break down the implementation:
Implement the shopping offers solution in different programming languages.
Below is the implementation of the shopping offers in different programming languages. Select a language tab to view the corresponding code.
123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140/** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Recursion with Memoization approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffers(price, special, needs) { // Memoization map to store results of subproblems const memo = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function dfs(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (memo.has(key)) { return memo.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + dfs(newNeeds)); } } // Memoize and return the result memo.set(key, result); return result; } return dfs(needs);} /** * Find the lowest price to buy exactly certain items with optimal use of special offers. * Dynamic Programming approach. * * @param {number[]} price - Array of prices for each item * @param {number[][]} special - Array of special offers * @param {number[]} needs - Array of needed quantities for each item * @return {number} - Lowest price */function shoppingOffersDP(price, special, needs) { // DP map to store results of subproblems const dp = new Map(); /** * Helper function to calculate the minimum price for the current needs. * * @param {number[]} currentNeeds - Current needed quantities * @return {number} - Minimum price */ function solve(currentNeeds) { // Convert currentNeeds to a string for memoization const key = currentNeeds.toString(); // If we've already computed the result for this state, return it if (dp.has(key)) { return dp.get(key); } // Option 1: Buy all items at their regular prices let result = 0; for (let i = 0; i < currentNeeds.length; i++) { result += currentNeeds[i] * price[i]; } // Option 2: Use a special offer for (const offer of special) { // Check if the offer is valid let valid = true; for (let i = 0; i < currentNeeds.length; i++) { if (currentNeeds[i] < offer[i]) { valid = false; break; } } if (valid) { // Update the needs const newNeeds = [...currentNeeds]; for (let i = 0; i < currentNeeds.length; i++) { newNeeds[i] -= offer[i]; } // Recursively solve the problem for the updated needs const offerPrice = offer[offer.length - 1]; result = Math.min(result, offerPrice + solve(newNeeds)); } } // Store the result in the DP table dp.set(key, result); return result; } return solve(needs);} // Test casesconsole.log(shoppingOffers([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffers([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0 console.log(shoppingOffersDP([2, 5], [[3, 0, 5], [1, 2, 10]], [3, 2])); // 14console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [1, 2, 1])); // 11console.log(shoppingOffersDP([2, 3, 4], [[1, 1, 0, 4], [2, 2, 1, 9]], [0, 0, 0])); // 0
Understand that we need to find the minimum cost to buy exactly the needed items, using special offers optimally.
Use recursion to explore all possible combinations of special offers and regular purchases, with memoization to avoid redundant calculations.
For each special offer, check if it's valid (i.e., it doesn't exceed our needs for any item).
If an offer is valid, update the needs by subtracting the items in the offer, and recursively solve the problem for the updated needs.
Also consider the option of not using any special offer and buying all items at their regular prices.
Modify the code to implement an alternative approach and test it with the same examples.
Implement a function that solves the shopping offers problem using a different approach than shown above.
Handle the case where there are no needed items (return 0).
Handle the case where there are no special offers (buy all items at their regular prices).
Handle the case where using special offers is not optimal (buy all items at their regular prices).