Find the Best Sightseeing Pair Last Updated : 31 May, 2024 Comments Improve Suggest changes Like Article Like Report Given an integer array arr[] where arr[i] represents the value of the ith sightseeing spot. Two sightseeing spots i and j have a distance j - i between them. The score of a pair (i < j) of sightseeing spots is arr[i] + arr[j] + i - j: the sum of arr[]of the sightseeing spots, minus the distance between them. Find the maximum score of a pair of sightseeing spots. Examples: Input: arr[]= {8, 1, 5, 2, 6}Output: 11Explanation: For i = 0, j = 2, arr[i] + arr[j] + i - j = 8 + 5 + 0 - 2 = 11 Input: arr= [1, 2]Output: 2Explanation: For i = 0, j = 1, arr[i] + arr[j] + i - j = 2 + 1 + 0 - 1 = 2 Approach: To solve the problem, follow the below idea: Since our task is to find max{ (arr[i]+i) + (arr[j]-j) } for all i<j. So we can say that we want maximum of arr[i]+i and maximum of arr[j]-j. Subproblem: find max (arr[i]-i) after i.Recurrence Relation: max_after(i) = max{ arr[i]-i, max_after(i+1) }.Finally ans would be maximum of arr[i]+i+max_after(i+1).Step-by-step algorithm: Maintain an array max_after[], such that max_after[i] stores the maximum value of arr[j] - j among all j >= i.Now, iterate from 0 to N - 1, and for every index i store the maximum value of arr[i] + i + max_after[i] and store it in ans.Return ans as the final answer.Below is the implementation of the above algorithm: C++ #include <bits/stdc++.h> using namespace std; int maxScoreSightseeingPair(vector<int>& arr) { // This function finds the best sightseeing pair in a // city represented by an array values. // - max_after: stores the maximum sightseeing score // obtainable starting from city i+1 int N = arr.size(); vector<int> max_after(N, 0); // Initialize max_after for the last city (no city after // it). max_after[N - 1] = arr[N - 1] - (N - 1); // Fill max_after array in reverse order. for (int i = N - 2; i >= 0; i--) { max_after[i] = max(max_after[i + 1], arr[i] - i); } int ans = 0; // Iterate through all cities except the last one. for (int i = 0; i < N - 1; i++) { // Calculate the total sightseeing score for the // current city and its best pairing city (i+1). ans = max(ans, arr[i] + i + max_after[i + 1]); } return ans; } int main() { // Driver code to test the function vector<int> arr = { 8, 1, 5, 2, 6 }; int maxScore = maxScoreSightseeingPair(arr); cout << "Max sightseeing score: " << maxScore << endl; return 0; } Java import java.util.Arrays; public class MaxScoreSightseeingPair { public static int maxScoreSightseeingPair(int[] arr) { // This function finds the best sightseeing pair in // a city represented by an array values. // - maxAfter: stores the maximum sightseeing score // obtainable starting from city i+1 int N = arr.length; int[] maxAfter = new int[N]; // Initialize maxAfter for the last city (no city // after it). maxAfter[N - 1] = arr[N - 1] - (N - 1); // Fill maxAfter array in reverse order. for (int i = N - 2; i >= 0; i--) { maxAfter[i] = Math.max(maxAfter[i + 1], arr[i] - i); } int ans = 0; // Iterate through all cities except the last one. for (int i = 0; i < N - 1; i++) { // Calculate the total sightseeing score for the // current city and its best pairing city (i+1). ans = Math.max(ans, arr[i] + i + maxAfter[i + 1]); } return ans; } public static void main(String[] args) { // Driver code to test the function int[] arr = { 8, 1, 5, 2, 6 }; int maxScore = maxScoreSightseeingPair(arr); System.out.println("Max sightseeing score: " + maxScore); } } // This code is contributed by Shivam Python def max_score_sightseeing_pair(arr): N = len(arr) max_after = [0] * N max_after[N - 1] = arr[N - 1] - (N - 1) for i in range(N - 2, -1, -1): max_after[i] = max(max_after[i + 1], arr[i] - i) ans = 0 for i in range(N - 1): ans = max(ans, arr[i] + i + max_after[i + 1]) return ans # Driver code to test the function arr = [8, 1, 5, 2, 6] max_score = max_score_sightseeing_pair(arr) print("Max sightseeing score:", max_score) JavaScript // Function to calculate the maximum score for a sightseeing pair function maxScoreSightseeingPair(arr) { // Get the length of the array const N = arr.length; // Initialize an array to store the maximum values after each index const maxAfter = new Array(N).fill(0); // Calculate the maximum value after each index maxAfter[N - 1] = arr[N - 1] - (N - 1); for (let i = N - 2; i >= 0; i--) { maxAfter[i] = Math.max(maxAfter[i + 1], arr[i] - i); } // Initialize a variable to store the maximum score let ans = 0; // Iterate through the array to find the maximum score for (let i = 0; i < N - 1; i++) { ans = Math.max(ans, arr[i] + i + maxAfter[i + 1]); } // Return the maximum score return ans; } // Driver code to test the function const arr = [8, 1, 5, 2, 6]; const maxScore = maxScoreSightseeingPair(arr); console.log("Max sightseeing score:", maxScore); // This code is contributed by Shivam Gupta OutputMax sightseeing score: 11 Time complexity: O(N), where N is the size of input subarray arr[].Auxiliary Space: O(N) Comment More infoAdvertise with us Next Article Types of Asymptotic Notations in Complexity Analysis of Algorithms V vforvikram Follow Improve Article Tags : Dynamic Programming DSA Arrays Google Practice Tags : GoogleArraysDynamic Programming Similar Reads Basics & PrerequisitesTime Complexity and Space ComplexityMany times there are more than one ways to solve a problem with different algorithms and we need a way to compare multiple ways. Also, there are situations where we would like to know how much time and resources an algorithm might take when implemented. To measure performance of algorithms, we typic 13 min read Types of Asymptotic Notations in Complexity Analysis of AlgorithmsWe have discussed Asymptotic Analysis, and Worst, Average, and Best Cases of Algorithms. The main idea of asymptotic analysis is to have a measure of the efficiency of algorithms that don't depend on machine-specific constants and don't require algorithms to be implemented and time taken by programs 8 min read Data StructuresGetting Started with Array Data StructureArray is a collection of items of the same variable type that are stored at contiguous memory locations. It is one of the most popular and simple data structures used in programming. Basic terminologies of ArrayArray Index: In an array, elements are identified by their indexes. Array index starts fr 14 min read String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut 2 min read Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The 2 min read Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Hereâs the comparison of Linked List vs Arrays Linked List: 2 min read Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first 2 min read Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems 2 min read Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most 4 min read Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of 3 min read Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this 15+ min read AlgorithmsSearching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input 2 min read Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ 3 min read Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution 14 min read Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get 3 min read Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net 3 min read Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of 3 min read Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit 4 min read AdvancedSegment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree 3 min read Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i 2 min read GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br 2 min read Interview PreparationInterview Corner: All Resources To Crack Any Tech InterviewThis article serves as your one-stop guide to interview preparation, designed to help you succeed across different experience levels and company expectations. Here is what you should expect in a Tech Interview, please remember the following points:Tech Interview Preparation does not have any fixed s 3 min read GfG160 - 160 Days of Problem SolvingAre you preparing for technical interviews and would like to be well-structured to improve your problem-solving skills? Well, we have good news for you! GeeksforGeeks proudly presents GfG160, a 160-day coding challenge starting on 15th November 2024. In this event, we will provide daily coding probl 3 min read Practice ProblemGeeksforGeeks Practice - Leading Online Coding PlatformGeeksforGeeks Practice is an online coding platform designed to help developers and students practice coding online and sharpen their programming skills with the following features. GfG 160: This consists of most popular interview problems organized topic wise and difficulty with with well written e 6 min read Problem of The Day - Develop the Habit of CodingDo you find it difficult to develop a habit of Coding? If yes, then we have a most effective solution for you - all you geeks need to do is solve one programming problem each day without any break, and BOOM, the results will surprise you! Let us tell you how:Suppose you commit to improve yourself an 5 min read Like