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    Qdm Assignment

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    Quantitative Decision Making Models Assignment # 2 QUESTION ONE Decision Variables Let‚ * X1 = number of full-time tellers * Y1 = number of part-time tellers starting at 9 a.m. (leaving at 1 p.m.) * Y2 = number of part-time tellers starting at 10 a.m. (leaving at 2 p.m.) * Y3 = numbers of part-time tellers starting at 11 a.m. (leaving at 3 p.m.) * Y4 = number of part-time tellers starting at noon ( leaving at 4 p.m.) * Y5 = number of part-time tellers starting at 1

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    CompilerOptimization

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    Introduction What optimization is? Optimization at different levels. Pareto principle & Hotspots When to Optimize? Automated and Manual Optimization Classification of optimization technique Optimizing Transformations What Optimization is? Definition:It is process of modifying a software system to make some aspect of it work more efficiently or use fewer resources. Main aim is to find superior algorithm. Optimization of a code to add n numbers Things we should take care during optimization Factors

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    Cashflow

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    Yinyu Ye‚ MS&E‚ Stanford MS&E310 Lecture Note #05 1 The Simplex Method Yinyu Ye Department of Management Science and Engineering Stanford University Stanford‚ CA 94305‚ U.S.A. http://www.stanford.edu/˜yyye (LY‚ Chapters 2.3-2.5‚ 3.1-3.4) Yinyu Ye‚ MS&E‚ Stanford MS&E310 Lecture Note #05 2 Geometry of linear programming Consider maximize subject to x1 x1 +2x2 ≤1 x2 ≤1 ≤ 1.5 ≥ 0. +x2 x2 x1 x1 ‚ Yinyu Ye‚ MS&E‚ Stanford MS&E310 Lecture Note #05 3

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    2011-2012 2012-2013 2011-2012 2012-2013 Current Ratio 2.5 2.5 3.4 4.0 Quick Ratio 0.5 -0.2 0.6 1.0 Long Term Debt to Equity 0.2 0.4 2.7 1.8 Inventory Turnover 12.9 10.0 9.3 8.6 Total Assets Turnover 1.4 1.4 1.4 1.4 Accounts Receivable Turnover 65.1 58.8 48.9 39.2 Average Collection Period 5.6 6.2 7.5 9.3 Gross Profit Margin 0.4 0.4 0.4 0.4 Net Profit Margin 0.0 0.0 0.0 0.0 Return on Total Assets (ROA) 0.0 0.1 0.1 0.1 Return on Equity (ROE) 0

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    CHAPTER 1: INTRODUCTION 1. Magnetic Abrasive Finishing (MAF) Surface roughness of parts produced by conventional machine tools‚ depends n the machine tool system and the cutting process. It is difficult to produce a smooth surface on complicated profiles at an economic cost by using conventional machining processes. This and the advent of new ‘ difficult-to-machine’ materials like hardened steel‚ nickel‚ cobalt‚ titanium alloys‚ ceramics‚ glass‚ etc.‚ have necessitated the need for

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    Chapter 18 Optimization Techniques Winter 2014 Agenda… 1) Functional Relationship 2) Marginal Analysis 3) Concept of a Derivative; Rules of Differentiation 4) The Marginal Cost = Marginal Revenue Rule 5) Constrained Optimization Functional relationships How an Economic Relationship is Expressed? By a Table‚ a Graph‚ or an Equation An Example of Functional Relationships (Table) CHERRY CORPORATION DAILY SALES 150 100 50 0 PER UNIT PRICE 10 20 30 40

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    Introduction Selection‚ Optimization‚ and Compensation Model (1%) The selective optimization with compensation model is that a person would select their best abilities that are most important to them and make them the best that they can be and the abilities that they choose to not focus on‚ they choose to let them go (Whitbourne‚ Whitbourne‚ & Konnert‚ 2015). Positive aging is when a person is facing adversity as part of the aging process but is dealing with their own challenges in their own way

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    building a compiler

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    compiler  So far we assumed that all the optimizations can be added to some existing tool chain.  Sometimes‚ a custom compiler is required‚ but: the effort for building a custom compiler is underestimated.  It is not sufficient to design a processor and then think about the compiler later.  Try to avoid the design of a full compiler. Approaches: - Modify an existing compiler. - Implement proposed optimizations as pre- or postpass optimization. - Use existing standard software components

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    COST OPTIMIZATION FOR WORKFORCE SCHEDULING An Operations Research Report IET4405 Submitted to Gregory Wiles By Group 3: Amanda Bathe Eminue Eminue Danielle Harmon Theophilus Holley Coltan Palmer Abigale Vining April 24‚ 2013 EXECUTIVE SUMMARY This report presents a recommendation for a hiring schedule that would allow Davis Instruments to hire temporary employees based on the product demand that varies from month to month for the six months of January to June‚ at the lowest

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    CHAPTER 2 Cuckoo Search Algorithm This chapter provides a breif introduction to the area of Nature Inspired Algorithms and its classification. Among all the categories‚ Swarm intelligence will be the main area of focus. Various swarm intelligence techinques will be discussed in the later sections. Cuckoo Search Algorithm is also one of the latest swarm intelligence technique which is focused in this dissertation to solve the problem discussed in chapter 1. 1. Nature Inspired Algorithms Nature has

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