Greedy algorithms
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Greedy algorithms work by making locally optimal choices at each step to arrive at a global optimal solution. They require that the problem exhibits the greedy choice property and optimal substructure. Examples that can be solved with greedy algorithms include fractional knapsack problem, minimum spanning tree, and activity selection. The fractional knapsack problem is solved greedily by sorting items by value/weight ratio and filling the knapsack completely. The 0/1 knapsack problem differs in that items are indivisible.
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Quick_sort1.pptxsandeep54552 Quick sort is a divide and conquer sorting algorithm that works by partitioning an array around a pivot value. It then recursively sorts the sub-arrays on each side of the pivot. The key steps are: 1) Choose a pivot element to divide the array; 2) Partition the array by swapping elements such that all elements less than the pivot come before it and all greater elements come after; 3) Recursively apply the same process to the sub-arrays on each side of the pivot until the entire array is sorted.
Link_List.pptx
Link_List.pptxsandeep54552 This document discusses different types of linked lists including singly linked lists, doubly linked lists, and circular linked lists. It describes the basic structure of nodes in each type of linked list and common operations like insertion, deletion, traversal, and searching. Circular linked lists are defined as lists where the last node points back to the first node, forming a continuous loop without a null terminator.
Templates in c++
Templates in c++sandeep54552 The document is a lecture by Professor Sandeep Vishwakarma. It does not provide any other details about the topic, content, or purpose of the lecture. The only information given is the name of the lecturer.
File handling in c++
File handling in c++sandeep54552 The document provides information about a lecture given by Prof. Sandeep Vishwakarma. No other details are provided about the topic of the lecture or its contents. The document only lists the name of the lecturer for an unspecified event.
Inheritance in c++ 
Inheritance in c++ sandeep54552 Prof. Sandeep Vishwakarma gave a lecture. The lecture was delivered by Prof. Sandeep Vishwakarma but no other details are provided about the topic, content, or audience of the lecture. The document only lists the name of the lecturer but gives no other informative context.
Constructor and Destructors in C++
Constructor and Destructors in C++sandeep54552 This document discusses different types of constructors in C++, including default, parameterized, and copy constructors. It provides examples of how to define each type of constructor and demonstrates their usage when creating objects. Destructors are also covered, along with an overview of their purpose to destroy objects and free allocated memory. Constructor overloading and the use of the "this" keyword in C++ are further explained with additional examples.
C++ programming introduction
C++ programming introductionsandeep54552 This document compares key differences between C and C++ programming languages. It lists 12 points of comparison between the two languages. Some key differences mentioned are:
1) C follows procedural programming while C++ supports both procedural and object-oriented programming.
2) C++ allows for better data encapsulation and security through access modifiers for class members.
3) C follows a top-down approach while C++ follows a bottom-up approach.
4) C++ supports features like function overloading, inheritance, exception handling, and namespaces that are not present in C.
Jsp tag library
Jsp tag librarysandeep54552 The document discusses the JSTL (JSP Standard Tag Library) which represents a set of tags to simplify JSP development. It provides advantages like fast development and code reusability. The core JSTL tags provide variable support and flow control. Common tags are outlined along with their purposes. Function, formatting, XML and SQL tags are also introduced and example uses are shown for SQL tags like <sql:setDataSource> and <sql:query> to connect to a database and execute queries.
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Greedy algorithms
- 2. Greedy Algorithm Introduction • "Greedy Method finds out of many options, but you have to choose the best option." • In this method, we have to find out the best method/option out of many present ways. • In this approach/method we focus on the first stage and decide the output, don't think about the future.
- 3. A greedy algorithm works if a problem exhibits the following two properties: Greedy Choice Property: A globally optimal solution can be reached at by creating a locally optimal solution. In other words, an optimal solution can be obtained by creating "greedy" choices. Optimal substructure: Optimal solutions contain optimal subsolutions. In other words, answers to subproblems of an optimal solution are optimal. Example: • machine scheduling • Fractional Knapsack Problem • Minimum Spanning Tree • Huffman Code • Job Sequencing • Activity Selection Problem
- 4. Steps for achieving a Greedy Algorithm • Feasible: Here we check whether it satisfies all possible constraints or not, to obtain at least one solution to our problems. • Local Optimal Choice: In this, the choice should be the optimum which is selected from the currently available • Unalterable: Once the decision is made, at any subsequence step that option is not altered.
- 5. Knapsack Problem- You are given the following- • A knapsack (kind of shoulder bag) with limited weight capacity. • Few items each having some weight and value. The problem states- Which items should be placed into the knapsack such that- • The value or profit obtained by putting the items into the knapsack is maximum. • And the weight limit of the knapsack does not exceed.
- 7. Knapsack Problem Variants- Knapsack problem has the following two variants- • Fractional Knapsack Problem • 0/1 Knapsack Problem
- 8. Fractional Knapsack Problem- In Fractional Knapsack Problem, • As the name suggests, items are divisible here. • We can even put the fraction of any item into the knapsack if taking the complete item is not possible. • It is solved using Greedy Method.
- 9. Fractional Knapsack Problem Using Greedy Method- Fractional knapsack problem is solved using greedy method in the following steps- Step-01: For each item, compute its value / weight ratio. Step-02: Arrange all the items in decreasing order of their value / weight ratio. Step-03: Start putting the items into the knapsack beginning from the item with the highest ratio.Put as many items as you can into the knapsack.
- 10. 0/1 Knapsack Problem- In 0/1 Knapsack Problem, • As the name suggests, items are indivisible here. • We can not take the fraction of any item. • We have to either take an item completely or leave it completely. • It is solved using dynamic programming approach.
- 11. • 3. You are given a knapsack that can carry a maximum weight of 60. There are 4 items with weights {20, 30, 40, 70} and values {70, 80, 90, 200}. What is the maximum value of the items you can carry using the knapsack? a) 160 b) 200 c) 170 d) 90
- 12. • 5. What is the time complexity of the brute force algorithm used to solve the Knapsack problem? a) O(n) b) O(n!) c) O(2n) d) O(n3)