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    Time Table Generation

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    of those NP hard problems. The problem can be solved using a heuristic search algorithm to find the optimal solution‚ but it only works for simple cases. For more complex inputs and requirements‚ finding a considerably good solution can take a while‚ or it may be impossible. This is where genetic algorithms come in to the game. In this article‚ I assume that you are familiar with the basic concepts of genetic algorithms‚ and I won’t describe them in detail because it has been done so many times before

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    "A parallel genetic algorithm for solving the school timetabling problem." In Proceedings of the 15th Australian Computer Science Conference‚ Hobart‚ 1-11. 3. Adam Marczyk (2004). "Genetic Algorithms and Evolutionary Computation ". Available online at http://www.talkorigins.org/faqs/genalg/genalg.html. 4. Al-Attar A.(1994). White Paper: "A hybrid GA-heuristic search strategy." AI Expert‚ USA. 5. Alberto Colorni‚ Marco Dorigo‚ Vittorio Manniezzo (1992). "A Genetic Algorithm to Solve the Timetable

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    Linear programming is a technique which shows practical problems as a series of mathematical equations which can be manipulated to find the optimum or best solution. Blending is a graphical approach to linear programming which deals with resource allocation subject to constraints. It is a model which assists firms in deciding the best possible utilisation of limited resources. Each resource constraint is represented as a mathematical linear equation. A linear expression is an equation which links

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    Tows mtrix Characteristic . TOWS analysis is an algorithm of the strategic analysis process‚ involving systematic and comprehensive assessment of external and internal factors that determine current condition and growth potential of the company. It is based on a simple classification scheme: all of the factors influencing the current and future position of the organization is divided into: External and internal to the organization‚ Having negative and positive impact on the organization. The intersection

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    TestLink

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    genetic algorithm approach Thomas S. Gruca a a‚1 ‚ Bruce R. Klemz b‚* Department of Marketing‚ University of Iowa‚ W376 Pappajohn Business Building‚ Iowa City‚ IA 52242-1000‚ USA b Department of Marketing‚ Winona State University‚ 101 Somsen‚ Winona‚ MN 55987‚ USA Received 23 March 1999; accepted 24 October 2001 Abstract Identifying an optimal positioning strategy for new products is a critical and difficult strategic decision. In this research‚ we develop a genetic algorithm based

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    removed by injecting penicillin for a week. But current techniques cannot discriminate between a lesion and an abscess .Our paper aims at distinguishing these two by astute measurement of their respective sizes using two algorithms –hill climbing algorithm‚ fuzzy C mean clustering algorithm aided by fundus photograph. Keywords: Abscission‚ Fuzzy C‚ Hill climbing‚ Endodontic therapy‚ Lesion‚ Gutta- percha. I INTRODUCTION Human teeth will be more prone to infection if it is void of any care. In the recent

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    7 sorting scheme

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    THE SEVEN SORTING SCHEME 1. BUBBLE SORT The bubble sort is generally considered to be the simplest sorting algorithm. Because of its simplicity and ease of visualization‚ it is often taught in introductory computer science courses. Because of its abysmal O(n2) performance‚ it is not used often for large (or even medium-sized) datasets. ALGORITHM: for i = 1:n‚ swapped = false for j = n:i+1‚ if a[j] < a[j-1]‚ swap a[j‚j-1] swapped = true

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    founded in 1988 by the “Dalle Molle” Foundation which promoted quality of life. Contents 1 Introduction 2 Routing in mobile ad hoc networks 3 Ant Colony Optimization for routing: general principles 4 The 4.1 4.2 4.3 4.4 4.5 AntHocNet routing algorithm Pheromone tables . . . . . . . . . . . . . . . . . Reactive route setup . . . . . . . . . . . . . . . Proactive route maintenance and improvement Data forwarding . . . . . . . . . . . . . . . . . Dealing with link failures . . . . . . . . . . .

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    (Cormen‚ Leiserson‚ and Rivest). What is algorithm design? Our text defines an algorithm to be any well-defined computational procedure that takes some values as input and produces some values as output. Like a cooking recipe‚ an algorithm provides a step-by-step method for solving a computational problem. A good understanding of algorithms is essential for a good understanding of the most basic element of computer science: programming. Unlike a program‚ an algorithm is a mathematical entity‚ which is independent

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    iSLIP Scheduling Algorithm Petros Mol Todor Ristov Nikolaos Trogkanis University of California‚ San Diego University of California‚ San Diego University of California‚ San Diego pmol@cs.ucsd.edu tristov@cs.ucsd.edu nikos@cs.ucsd.edu ABSTRACT High throughput and fairness consist two desirable properties when scheduling traffic in an Input-Queued crossbar switch. Unfortunately‚ these two goals are conflicting which makes the job of most scheduling algorithms that want to

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