Automatic Frequency Planning and Optimization Algorithm for Cellular Networks Muhammad Umair‚ Waleed Bin Shahid‚ Masab Javed Abbasi‚ Department of Electrical Engineering Royal Institute of Technology (KTH) SE100-44 Stockholm‚ SWEDEN E-mail: mumair@kth.se‚ waleed.shahid@mcs.edu.pk ‚ masab.abbasi-pc@telenor.com.pk Abstract— Frequency planning in ever growing cellular networks is an extremely arduous task. Any effort to lay down manual frequency plans promulgates inefficiency in the cellular
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Management Implementation of Pricing and Revenue Optimization Introduction Perhaps one of the most difficult managerial decisions in the 21st century is the decision to make a decision. Analysis paralysis‚ endless meetings‚ and corporate structure have made it painstakingly difficult to come to any real conclusions. So when the Chief Financial Officer‚ Bruce Berman‚ of Bloomindale’s was tasked with decision to implement ProfitLogic’s Pricing Optimization (PO) system‚ he called upon Daniel Gabbay‚ an
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Chapter 2 ECONOMIC OPTIMIZATION QUESTIONS & ANSWERS Q2.1 In 2004‚ the second-largest U.S. long-distance telephone company eliminated about 2‚000 jobs at four call centers in Colorado‚ Iowa‚ Kansas‚ and South Carolina. "MCI must continue to revamp its cost structure to better position the company for future success‚" a company spokesperson said. Does this decision reflect an application of the global or partial optimization concept? Explain. ANSWER MCI=s decision to scale back employment at four
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Tutorial: Using Excel for Linear Optimization Problems Part 1: Organize Your Information There are three categories of information needed for solving an optimization problem in Excel: an Objective Function‚ Decision Variables‚ and Constraints. It is simplest to organize these on paper before you start working with the spreadsheet. For tutorial purposes we will follow an example‚ “The Cargo Problem”‚ from start to finish: A shipping company has the capacity to move 100 tons of cargo per day by air
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Proposal – Generalizations of Newsvendor Problem 1. Introduction: The newsvendor model has been used in operations management and applied economics for years to determine optimal ordering quantity under uncertain demand. Perishable goods such as banana and lettuce cannot be carried from one period to another. Managers have to make decision on the inventory level of perishable goods over a very limited period. For example‚ due to the uncertainty of the demand of the newspaper‚ the newsboy
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A Project Report On [………………Project Title…………….] Submitted in partial fulfillment of the Requirements for the award of degree of Bachelor of Technology In Computer Science and Engineering By [Name of the Student] [H.T.NO:12H61A0.....] Under the guidance of Mr. / Mrs./Ms. Guide Name Designation‚ CSE Dept. [pic] Department of Computer Science and Engineering‚ Anurag
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Recent developments in optimization techniques that deals in finding the solution of combinatorial optimization problems has provided engineering designers new capabilities. These new optimization algorithms are called metaheuristic techniques and they use nature as a source of inspiration to develop new numerical optimization procedures. It is shown in the literature that these techniques are robust and efficient and their performance is not affected by the complexity of optimization problems. In last
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Int. J. Production Economics 141 (2013) 529–540 Contents lists available at SciVerse ScienceDirect Int. J. Production Economics journal homepage: www.elsevier.com/locate/ijpe Postponed product differentiation with demand information update$ Juliang Zhang a‚ Biying Shou b‚n‚ Jian Chen c a b c Department of Logistics Management‚ School of Economics and Management‚ Beijing Jiaotong University‚ Beijing 100044‚ China Department of Management Sciences‚ City University of Hong Kong‚ Hong
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decision making process for different strategies‚ but after taking Operations Research‚ I know that I am better equipped to understand and formulate optimal implementation solutions. This case uses mixed integer programming‚ and to solve the optimization problems‚ I used LINGO 11.1. Case Background We have been given the implementation schedule‚ as follows: Month Department Month 1 None Month 2 Sales Month 3 Manufacturing Month 4 Warehouse Month 5 Marketing In month
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Noname manuscript No. (will be inserted by the editor) PSO Algorithm for the Traveling Salesman and Other Optimization Problems. An OpenMp Implementation Santiago Garcia Carbajal · Fiona Reid · David Corne Received: date / Accepted: date Abstract Particle Swarm Optimization is a general purpose optimization method due to Kennedy‚ Eberhart and Shi. It works by maintaining a swarm of particles moving around the search space influenced by the observed improvements of the other particles. The
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