built-in optimization tool called Solver. Now we demonstrate how to use Excel spreadsheet modeling and Solver to find the optimal solution of optimization problems. If the model has two variables‚ the graphical method can be used to solve the model. Very few real world problems involve only two variables. For problems with more than two variables‚ we need to use complex techniques and tedious calculations to find the optimal solution. The spreadsheet and solver approach makes solving optimization problems
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Simply put‚ it is computer-guided trading‚ where a program with direct market access can monitor the market and order trades when certain conditions are met. Earlier‚ the trading strategies were executed by humans but now it is majorly done by algorithms thus removing human emotion element in trading. Now‚ you may be thinking who uses this concept? Well‚ Algorithmic trading is widely used by investment banks‚ pension funds‚ mutual funds‚ and other buy-side (investor-driven) institutional traders
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Flowchart is a diagrammatic representation of an algorithm. Flowchart is very helpful in writing program and explaining program to others. An algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithm is a step-by-step procedure for calculations. A flowchart is a type of diagram that represents an algorithm‚ workflow or process‚ showing the steps as boxes of various kinds‚ and their order by connecting them with arrows. Types of
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prior to completing the lab. Write a program that will calculate the cost of installing fiber optic cable at a cost of .87 per ft for a company. Your program should display the company name and the total cost. Step 1: Examine the following algorithm as a base for how the program should flow. (Reference: Designing a Program‚ page 31). 1. Display a welcome message for your program. 2. Get the company name. 3. Get the number of feet of fiber optic to be installed. 4. Multiply the total cost
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Operational research is an interdisciplinary idea that uses thinking and also methods such as mathematical modeling‚ statistics and algorithms to arrive at optimal or near optimal solutions to complex problems in an organization. In an operational research project there are 5 phases‚ namely‚ problem identification‚ formulating problem‚ deriving solution validating model and lastly‚ the implementation of results. The first phase is to identify the problem through the observation of its symptoms
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NP-hard problems and mentioned about what is NP-hard problems. One of classical NP-hard problems which could not be solved within the polynomial computation time is a cutting stock problem. Wongprakornkul and Charnsethikul said that the most powerful algorithm for solving linear problems with many columns is the column generation procedure and after they give some information about large size of the pattern in cutting stock problems. In the study‚ they proposed to approach; first one is column generation
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STATEMENT OF PURPOSE l I did very well during my undergraduate studies at the prestigious R. V. College of Engineering‚ Bangalore (www.rvce.com) securing the 7th rank among 2000 mechanical engineering students in the Bangalore University. As part of the curriculum requirements‚ I worked on the analysis of Wildhaber-Novikov gears for defense applications. The project was adjudged as one of the best projects in the college and was awarded maximum marks during evaluation (for a description please
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Analysis of Algorithms 07/29/13 CS202 - Fundamentals of Computer Science II 1 Algorithm • An algorithm is a set of instructions to be followed to solve a problem. – There can be more than one solution (more than one algorithm) to solve a given problem. – An algorithm can be implemented using different prog. languages on different platforms. • Once we have a correct algorithm for the problem‚ we have to determine the efficiency of that algorithm. – – How much time that algorithm
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independently from learning programming. For this purpose we use problems that are not easy to solve but have an easily understandable problem definition. A proper visualization of these problems can help to understand the basic concepts connected with algorithms: correctness‚ termination‚ efficiency‚ determinism‚ parallelism‚ etc. The presented examples were used by the author in a pre-university course‚ they may also be used in secondary schools to help understanding some concepts of computer science.
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ECO 204 2010 - 2011 Sayed Ajaz Hussain Lecture 1 Ajaz Hussain. Department of Economics. University of Toronto (St. George) 1 Today About ECO 204 (Single-Variable) Functions (Single-Variable) Calculus (Single-Variable) Unconstrained Optimization (Single-Variable) Concave and Convex Functions Ajaz Hussain. Department of Economics. University of Toronto (St. George) 2 Instructor: Office Room 212‚ Economics Department 150 St. George Street Office hours Thursdays 1 – 3 pm or by appointment
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