TAILIEUCHUNG - Lecture Algorithms and data structures: Chapter 9 - Sorting Algorithms

An Abstract List (or List ADT) is linearly ordered data where the programmer explicitly defines the ordering. We will now look at our first abstract data structure: Relation - explicit linear ordering, operations, implementations of an abstract list with linked lists and arrays, memory requirements, strings as a special case, the STL vector class. | Review Selection Sort Selection Sort Algorithm Time Complexity Best case Average case Worst case Examples Sorting Algorithms There are many sorting algorithms, such as: Selection Sort Insertion Sort Bubble Sort Merge Sort Quick Sort The first three are the foundations for faster and more efficient algorithms. Sorting Sorting is a process that organizes a collection of data into either ascending or descending order. An internal sort requires that the collection of data fit entirely in the computer’s main memory. We can use an external sort when the collection of data cannot fit in the computer’s main memory all at once but must reside in secondary storage such as on a disk. We will analyze only internal sorting algorithms. Any significant amount of computer output is generally arranged in some sorted order so that it can be interpreted. Sorting also has indirect uses. An initial sort of the data can significantly enhance the performance of an algorithm. Majority of programming projects use a sort somewhere, and in many cases, the sorting cost determines the running time. A comparison-based sorting algorithm makes ordering decisions only on the basis of comparisons. Selection Sort The list is divided into two sublists, sorted and unsorted, which are divided by an imaginary wall. We find the smallest element from the unsorted sublist and swap it with the element at the beginning of the unsorted data. After each selection and swapping, the imaginary wall between the two sublists move one element ahead, increasing the number of sorted elements and decreasing the number of unsorted ones. Each time we move one element from the unsorted sublist to the sorted sublist, we say that we have completed a sort pass. A list of n elements requires n-1 passes to completely rearrange the data. 23 78 45 8 32 56 8 78 45 23 32 56 8 23 45 78 32 56 8 23 32 78 45 56 8 23 32 45 78 56 8 23 32 45 56 78 Original List After pass 1 After pass 2 After pass 3 After pass 4 After pass 5 Sorted .

• Cơ sở dữ liệu
• Algorithm analysis
• Graph algorithms
• Design techniques
• Data structures
• Lecture Algorithms and data structures
• Algorithm analysis
• Design techniques
• Cấu trúc dữ liệu
• Algorithm analysis in C++
• The disjoint sets class
• Algorithm design techniques
• Amortized analysis
• Advanced data structures
• Advanced Algorithms Analysis and Design
• Lecture Advanced Algorithms Analysis and Design
• Bài giảng Phân tích và thiết kế thuật toán nâng cao
• The Floyd Warshall algorithm
• Johnson’s algorithm
• Bellman Ford algorithm
• Algorithm design
• Lecture Algorithm design
• Computational tractability
• Asymptotic order of growth
• Polynomial running time
• Dynamic programming
• Hirschbergs algorithm
• Greedy Algorithms
• Dijkstras algorithm
• Minimum spanning trees
• Network flow
• Ford Fulkerson algorithm
• Max flow min cut theorem
• Analysis in C++
• A general overview
• Extendible hashing
• Hash tables in the standard library
• Performance analysis of a sugar plant using genetic algorithm
• Optimization of crystallization system of a sugar plant using genetic algorithm
• A sugar plant using genetic algorithm
• Refining system fails
• The crystallization system includes crystallization units
• Local search
• Gradient descent
• Metropolis algorithm
• Analysis of Algorithm
• Incorrect algorithms
• Analyzing an algorithm
• nalyzing an algorithm
• The correct output
• Communication bandwidth
• Computational time
• A practical introduction
• Mathematical preliminaries
• Binary trees
• Non binary trees
• Internal sorting
• Graph search
• Graph connectivity
• Graph traversal
• Coin changing
• Optimal caching
• Counting inversions
• Closest pair of points
• Randomized quicksort
• Master theorem
• Integer multiplication
• Matrix multiplication
• Weighted interval scheduling
• Knapsack problem
• Bipartite matching
• Disjoint paths
• Assignment problem
• Input queued switching
• Poly time reductions
• Constraint satisfaction problems
• Graph coloring
• Decision problems
• NP complete
• Nondeterministic polynomial
• PSPACE complexity class
• Quantified satisfiability
• PSPACE complete
• Vertex covers
• Bipartite graphs
• Limits of tractability
• Approximation Algorithms
• Vertex cover
• Randomized Algorithms
• Contention resolution
• Linearity of expectation
• Performance analysis of a real time adaptive prediction algorithm
• Real time adaptive prediction algorithm for traffic congestion
• Lower Mean Square Error
• The actual traffic congestion states