Backtracking is an algorithm that systematically searches for solutions to a problem by exploring all potential candidates. It works by assuming solutions can be represented as vectors, and traversing the domain of these vectors in a depth-first manner until it finds solutions. When a partial vector is found not to represent a partial solution, it backtracks by removing the last value added and trying alternative values. Examples where backtracking can be applied include the traveling salesperson problem and the n queens problem.
Graph theory - Traveling Salesman and Chinese PostmanChristian Kehl
Traveling Salesman and Chinese Postman problems
1. Problem Description and Complexity
2. Theoretical Approach
3. Practical Approaches and Possible Solutions
4. Examples
Analysis & Design of Algorithms
Backtracking
N-Queens Problem
Hamiltonian circuit
Graph coloring
A presentation on unit Backtracking from the ADA subject of Engineering.
One of the main reasons for the popularity of Dijkstra's Algorithm is that it is one of the most important and useful algorithms available for generating (exact) optimal solutions to a large class of shortest path problems. The point being that this class of problems is extremely important theoretically, practically, as well as educationally.
Graph theory - Traveling Salesman and Chinese PostmanChristian Kehl
Traveling Salesman and Chinese Postman problems
1. Problem Description and Complexity
2. Theoretical Approach
3. Practical Approaches and Possible Solutions
4. Examples
Analysis & Design of Algorithms
Backtracking
N-Queens Problem
Hamiltonian circuit
Graph coloring
A presentation on unit Backtracking from the ADA subject of Engineering.
One of the main reasons for the popularity of Dijkstra's Algorithm is that it is one of the most important and useful algorithms available for generating (exact) optimal solutions to a large class of shortest path problems. The point being that this class of problems is extremely important theoretically, practically, as well as educationally.
A Hamiltonian path is a path that visits each vertex of the graph exactly once.
A Hamiltonian circuit is a path that uses each vertex of a graph exactly once and returns to the starting vertex.
The string matching problem is a classic of algorithms. In this class, we only look at the Rabin-Karpp algorithm as a classic example of the string matching algorithms
This is an introduction to Analytic Combinatorics. I gave this talk as part of the PSS the 9 October 2014 at the University of Bath... needless to say I threw in a couple of hipster jokes.
Convex Hull - Chan's Algorithm O(n log h) - Presentation by Yitian Huang and ...Amrinder Arora
Chan's Algorithm for Convex Hull Problem. Output Sensitive Algorithm. Takes O(n log h) time. Presentation for the final project in CS 6212/Spring/Arora.
A Hamiltonian path is a path that visits each vertex of the graph exactly once.
A Hamiltonian circuit is a path that uses each vertex of a graph exactly once and returns to the starting vertex.
The string matching problem is a classic of algorithms. In this class, we only look at the Rabin-Karpp algorithm as a classic example of the string matching algorithms
This is an introduction to Analytic Combinatorics. I gave this talk as part of the PSS the 9 October 2014 at the University of Bath... needless to say I threw in a couple of hipster jokes.
Convex Hull - Chan's Algorithm O(n log h) - Presentation by Yitian Huang and ...Amrinder Arora
Chan's Algorithm for Convex Hull Problem. Output Sensitive Algorithm. Takes O(n log h) time. Presentation for the final project in CS 6212/Spring/Arora.
Backtracking is a general algorithm for finding all (or some) solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons each partial candidate c ("backtracks") as soon as it determines that c cannot possibly be completed to a valid solution.
Backtracking is a general algorithm for finding all (or some) solutions to some computational problems, notably constraint satisfaction problems, that incrementally builds candidates to the solutions, and abandons each partial candidate c ("backtracks") as soon as it determines that c cannot possibly be completed to a valid solution.
I am Travis W. I am a Computer Science Assignment Expert at programminghomeworkhelp.com. I hold a Master's in Computer Science, Leeds University. I have been helping students with their homework for the past 9 years. I solve assignments related to Computer Science.
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N-Queens Combinatorial Problem - Polyglot FP for Fun and Profit – Haskell and...Philip Schwarz
First see the problem solved using the List monad and a Scala for comprehension.
Then see the Scala program translated into Haskell, both using a do expressions and using a List comprehension.
Understand how the Scala for comprehension is desugared, and what role the withFilter function plays.
Also understand how the Haskell do expressions and List comprehension are desugared, and what role the guard function plays.
Scala code for Part 1: https://github.com/philipschwarz/n-queens-combinatorial-problem-scala-part-1
Errata: on slide 30, the resulting lists should be Haskell ones rather than Scala ones.
BackTracking Algorithm: Technique and ExamplesFahim Ferdous
This slides gives a strong overview of backtracking algorithm. How it came and general approaches of the techniques. Also some well-known problem and solution of backtracking algorithm.
Narrow sieves, representative sets and divide-and-color are three breakthrough techniques related to color coding, which led to the design of extremely fast parameterized algorithms. In this talk, I will discuss the power and limitations of these techniques. I will also briefly address some recent developments related to these techniques, including general schemes for mixing them.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
2. Backtracking is a refinement of the brute force approach, which
systematically searches for a solution to a problem among all
available options. It does so by assuming that the solutions are
represented by vectors (v1,v2, ..., vm) of values and by traversing, in a
depth first manner, the domains of the vectors until the solutions are
found.
When invoked, the algorithm starts with an empty vector. At each
stage it extends the partial vector with a new value. Upon reaching a
partial vector (v1,v2, ..., vi) which can’t represent a partial solution, the
algorithm backtracks by removing the trailing value from the vector,
and then proceeds by trying to extend the vector with alternative
values.
3. ALGORITHM :
try(v1,v2, ..., vi){
IF (v1,v2, ..., vi) is a solution
THEN RETURN (v1,v2, ..., vi)
FOR each v DO
IF (v1,v2, ..., vi,v) is acceptable vector
THEN sol = try(v1,v2, ..., vi,v)
IF sol ≠ () THEN RETURN sol
END
END
RETURN ()
}
4. If Si is the domain of vi , then S1 × ... × Sm is the solution space of
the problem. The validity criteria used in checking for acceptable
vectors determines what portion of that space needs to be searched,
and so it also determines the resources required by the algorithm.
The traversal of the solution space can be represented by a depth-
first traversal of a tree. The tree itself is rarely entirely stored by the
algorithm in discourse; instead just a path toward a root is stored, to
enable the backtracking.
5.
6. 1. Traveling Salesperson
The problem assumes a set of n cities, and a salesperson which needs
to visit each city exactly once and return to the base city at the end.
The solution should provide a route of minimal length. The route (a,
b, d, c) is the shortest one for the following one, and its length is 51.
7.
8. The traveling salesperson problem is an NP-hard problem, and so no
polynomial time algorithm is available for it. Given an instance G =
(V, E) the backtracking algorithm may search for a vector of cities (v1,
..., v|V|) which represents the best route.
The validity criteria may just check for number of cities in of the
routes, pruning out routes longer than |V|. In such a case, the
algorithm needs to investigate |V||V| vectors from the solution space.
9.
10.
11. On the other hand, the validity criteria may check for repetition of
cities, in which case the number of vectors reduces to |V |!.
12.
13. THE N QUEENS PROBLEM
Consider a n by n chess board, and the problem of placing n queens
on the board without the queens threatening one another.
The solution space is {1, 2, 3, ..., n}n. The backtracking algorithm may
record the columns where the different queens are positioned. Trying
all vectors (p1, ..., pn) implies nn cases. Noticing that all the queens
must reside in different columns reduces the number of cases to n!.
For the latter case, the root of the traversal tree has degree n, the
children have degree n - 1, the grand children degree n - 2, and so
forth.
14.
15. The solution space is {1, 2, 3, ..., n}n. The backtracking algorithm may
record the columns where the different queens are positioned. Trying
all vectors (p1, ..., pn) implies nn cases. Noticing that all the queens
must reside in different columns reduces the number of cases to n!.
For the latter case, the root of the traversal tree has degree n, the
children have degree n - 1, the grand children degree n - 2, and so
forth.