"Optimization algorithms" Essays and Research Papers

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    Shaker Sort Algorithm

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    “Shaker Sort Algorithm” History Features Algorithm/Process Implementation 1. Pseudo code 2. Flowchart 3. Other programs Sample case study History of shaker sort Shaker Sort (implemented by Jason Harrison) Shaker Sort is like Selection Sort in that it passes over the unsorted part of the array to select the next element(s) to add to the sorted part. It differs in that with each pass it looks for the smallest and the largest remaining element. It then moves the smallest element into its

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    Algorithms Test

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    Pradeep reddy Pinninti - 85025 1- Depth-first search always expands at least as many nodes as A* search with an admissible heuristic FALSE. Depth-first search may possibly‚ sometimes‚ expand fewer nodes than A* search with an admissible heuristic. E.g.‚ it is logically possible that sometimes‚ by good luck‚ depth-first search may march directly to the goal with no back-tracking. 2- h(n) = 0 is an admissible heuristic for the 8-puzzle TRUE. h(n)=0 NEVER over-estimates the remaining optimal distance

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    An algorithm‚ according to the Random House Unabridged Dictionary‚ is a set of rules for solving a problem in a finite number of steps. One of the fundamental problems of computer science is sorting a set of items. The solutions to these problems are known as sorting algorithms and rather ironically‚ “the process of applying an algorithm to an input to obtain an output is called a computation” [http://mathworld.wolfram.com/Algorithm.html]. The quest to develop the most memory efficient and

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    Selection Sort 1. array to be sorted: A 2. array to be returned: B 3. find smallest element in A and put in B 4. mark space in A with null so it won’t be chosen again 5. repeat last two steps until B is sorted array 3. Insertion Sort 1. algorithm passes through each element everything before element is sorted puts element in appropriate place in sorted half of array by checking each element starting from the back of the sorted part of the array 2. Code Methods: insertionsort 3. Worst

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    sample of Scope and Limitation. This was used on a CASE STUDY entitled “Comparison and Contrast of sorting algorithm between Visual Basic.net and Java (Netbeans)”. This will help you to construct your own scope and limitation according to your study. This will serve only as your overview and guide for this part of case study. SAMPLE SCOPE AND LIMITATION: COMPARISON AND CONTRAST OF SORTING ALGORITHM BETWEEN VISUAL BASIC.NET AND JAVA (NETBEANS) Scope and Limitation Scope The study

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    Purchase TCO #2– Given a simple business problem‚ design a solution algorithm that uses arithmetic expressions and built-in functions. Assignment: Your goal is to solve the following simple programming exercise. You have been contracted by a local restaurant to design an algorithm determining the total meal charges. The algorithm should ask the user for the total food purchase and the tip percent. Then‚ the algorithm will calculate the amount of a tip‚ a 7% sales tax‚ and the total meal

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    queuing (FQ) algorithm to mainly provide 1) fair allocation of bandwidth‚ 2) lower delay for sources using less than their full share of bandwidth‚ and 3)protection from ill-behaved sources. They argue that First-Come-First-Serve (FCFS) queuing is not adequate; more discriminating queuing algorithms must be used in conjunction with source flow control algorithms to control congestion effectively in noncooperative environments. While designing algorithm they consider

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    Introduction to Genetic Algorithms S.N.Sivanandam · S.N.Deepa Introduction to Genetic Algorithms With 193 Figures and 13 Tables Authors S.N.Sivanandam Professor and Head Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN‚ India S.N.Deepa Ph.D Scholar Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN‚ India Library of Congress Control Number: 2007930221 ISBN 978-3-540-73189-4 Springer Berlin Heidelberg

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    COMPARISMS OF OPTIMIZATION STRATEGIES FOR THE TRAVELLING SALESMAN PROBLEM Department of Information Systems and Computing B.Sc. (Hons) Computer Science‚ Artificial Intelligence Academic Year 2012-2013 Comparison of Optimization Strategies for the Travelling Salesman Problem Adewale Oluwaseun Mako (0941620) A Report Submitted in the partial fulfilment of the requirement for the degree of Bachelor of Science Brunel University Department of Information Systems and Computing Uxbridge

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    Quickselect algorithm implementation A project report submitted in partial fulfillment of the requirements of Algorithms Design Course (ICS353) for the completion of degree of Bachelor of Science in Computer Engineering The Computer Science Department King Fahd University of Petroleum and Minerals January‚ 2011 ABSTRACT Sorting and selection is widely used by computer applications intermediary to finish tasks like searching. QUICKSELECT algorithm is known to be among fastest selection

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