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    decision-making bringing out limitations‚ if any. 2. Explain the concept and computational steps of the simplex method for solving linear programming problems. How would you identify whether an optimal solution to a problem obtained using simplex algorithm is unique or not? a) What is the difference between a feasible solution‚ a basic feasible solution‚ and an optimal solution of a linear programming problem? b) What is the difference between simplex solution procedure for a `maximization’ and

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    Linear Programming

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    TOPIC; LINEAR PROGRAMMING DATE; 5 JUNE‚ 14 UNIVERSITY OF CENTRAL PUNJAB INTRODUCTION TO LINEAR PROGRAMMING Linear programming (LP; also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships. Linear programming is a special case of mathematical programming. It

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    modifying the district plan from a six-ward system with two council members in each to a single-member 12-ward system. The authors of this paper designed the redistricting plan. This paper describes the algorithm we applied to solve the problem and the decision support system we used. The algorithm is based on a multicriteria mathematical model‚ which is solved by a tabu search heuristic embedded within a geographic information system (GIS)-based decision support system. The resulting district plan

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    Operations Research

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    programming problem. 5 Using Lagrange multiplier method solve following problem: Minimize f (X) = 1/2(x12 + x22 + x32). subject to constraints: g1(x) = x1 − x2 = 0. g2(x) = x1 + x2 + x3 − 1 = 0. 6 (a) (b) Explain method of multipliers algorithm. Describe briefly differences between the MOM and other transformation methods such as SUMT. Contd. in Page 2 www.jntuworld.com www.jntuworld.com www.jwjobs.net 1 Code: 9A05603 Page 2 7

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    Algorithm Analysis and Design NP-Completeness Pham Quang Dung Hanoi‚ 2012 Pham Quang Dung () Algorithm Analysis and Design NP-Completeness Hanoi‚ 2012 1 / 31 Outline 1 Easy problems - class P Decision problems vs. Optimization problems Class NP Reductions NP-complete class 2 3 4 5 Pham Quang Dung () Algorithm Analysis and Design NP-Completeness Hanoi‚ 2012 2 / 31 Class P: Problems that are solvable by polynomial-time algorithms (O(nk ) where n

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    present a high performance recovery algorithm for distributed systems in which checkpoints are taken asynchronously. It offers fast determination of the recent consistent global checkpoint (maximum consistent state) of a distributed system after the system recovers from a failure. The main feature of the proposed recovery algorithm is that it avoids to a good extent unnecessary comparisons of checkpoints while testing for their mutual consistency. The algorithm is executed simultaneously by all

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    SEM optimization

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    AEM 4550: Economics of Advertising HW3 – Due at the beginning of the class Monday‚ March 8th You are encouraged to work in groups of 3-4 students. Write legibly‚ type when you can. Include a title page‚ listing the homework number and the names of all the members of the study group. PARTS I & II ANSWERS Objective: to analyze online advertising effectiveness. This question deals with the case “Air France Internet Marketing: Optimizing Google‚ Yahoo!‚ MSN‚ and Kayak Sponsored Search” by

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    Computer

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    skills through a “hands-on” approach to writing‚ testing‚ and debugging computer programs. Students will develop analytical skills‚ along with a solid foundation in several computer programming languages‚ through the analysis of generalized computer algorithms. The Business Computer Information Science Program offers students an opportunity to develop computer skills in a business environment. Through theoretical discussions and a “handson” approach‚ students will explore the integration of business and

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    completion of this tutorial/lab‚ you should be able to: Identify inputs‚ outputs‚ and processing components from a problem description. Work out solution algorithm for the defined problem with sequence‚ selection and repetition control structures. Write the solution algorithm with pseudocode. Task 1: Tutorial Short Questions. Task 2: Algorithms Development Problem 1. A simple problem with only sequence Problem 2. A problem with single selection Problem 3. A problem with multiple selections Problem

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    Motion Detection

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    SIMULINK models for tracking single and multiple objects. We present various algorithms for tracking objects and determining the velocity of moving object in sequence of frames. Using the segmentation technique we can locate a target in the current frame. Target localization in current frame was computationally much complex in the conventional algorithms. Searching an object in the current frame using these algorithms starts from its location of the previous frame in the basis of attraction probably

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