See Question.pdf

**Subject Computer Science Data Structures and Algorithms**

See Question.pdf

This material may consist of step-by-step explanations on how to solve a problem or examples of proper writing, including the use of citations, references, bibliographies, and formatting. This material is made available for the sole purpose of studying and learning - misuse is strictly forbidden.

Report

Brief Introduction of the Used Algorithm

The algorithm used for finding the single source shortest path in this project is based on Bellman-Ford’s approach. Among the most-known applications can be highlighted the RIP (Routing Information Protocol) and network flow analysis (for cycle cancellation).

The present algorithm is used to discover the shortest paths from a single source node to the other vertices. A strong point is represented by the fact that it is usable in a weighted directed graph; although it performs slower than classical Dijkstra’s algorithm it is applicable in a wider range of situations because it can handle graphs where some of the edge weights are negative numbers.

The “relaxation” is applied by |V|-1 times to all edges (V is the number of nodes of the initial graph). At each step the number of nodes (having the distance correctly calculated) grows and in the end all vertices have their correct distances assigned....

Brief Introduction of the Used Algorithm

The algorithm used for finding the single source shortest path in this project is based on Bellman-Ford’s approach. Among the most-known applications can be highlighted the RIP (Routing Information Protocol) and network flow analysis (for cycle cancellation).

The present algorithm is used to discover the shortest paths from a single source node to the other vertices. A strong point is represented by the fact that it is usable in a weighted directed graph; although it performs slower than classical Dijkstra’s algorithm it is applicable in a wider range of situations because it can handle graphs where some of the edge weights are negative numbers.

The “relaxation” is applied by |V|-1 times to all edges (V is the number of nodes of the initial graph). At each step the number of nodes (having the distance correctly calculated) grows and in the end all vertices have their correct distances assigned....

This is only a preview of the solution. Please use the purchase button to see the entire solution

Two Dynamic Programming Algorithms: Rod Cutting & Minimum Number of Coins Change

$18.00

Dynamic

Programming

Algorithm

Complexity

Recurrence

Rod

Cut

Coin

Change

Amount

Integer

Denomination

Pseudocode

Maximum

DP

Sale

Unit

Piece

Price

Table

Bottom-up

Example

Analysis

Base

Case

Dynamic

Programming

Algorithm

Complexity

Recurrence

Rod

Cut

Coin

Change

Amount

Integer

Denomination

Pseudocode

Maximum

DP

Sale

Unit

Piece

Price

Table

Bottom-up

Example

Analysis

Base

Case

MergeSort Algorithm Applied to the E, X, A, M, P, L, E List

$5.00

Computer Science

Data Structures

Merge-sort

Mergesort

Algorithm

Pseudo

Code

Alphabetical

Order

List

Two Problems with Partition Sum and Undirected & Unweighted Graph Properties

$15.00

Partition

Problem

Sum

Equal

Solution

Largest

Independent

Set

Undirected

Unweighted

Euler

Cycle

Hamilton

Graph

Counting Inversions (Swaps) in Insertion Sort Algorithm

$8.00

Insertion

Sort

Algorithm

Inversion

Swap

Count

Pair

Computer Science

Data Structures

Algorithms Assignment

$1.00

Algorithm

Computer Science

Graphs

Programming Language

Programming

Analysis