...• Linear Programming Supplement E TRUE/FALSE 1. Linear Programming Linear programming is useful for allocating scarce resources among competing demands. Answer: True Reference: Introduction Difficulty: Easy Keywords: linear programming, scarce resources, competing demands A constraint is a limitation that restricts the permissible choices. Answer: True Reference: Basic Concepts Difficulty: Moderate Keywords: constraint, limit Decision variables are represented in both the objective function and the constraints while formulating a linear program. Answer: True Reference: Basic Concepts Difficulty: Moderate Keywords: constraint, decision variable, objective function A parameter is a region that represents all permissible combinations of the decision variables in a linear programming model. Answer: False Reference: Basic Concepts Difficulty: Moderate Keywords: parameter, decision variable, feasible region In linear programming, each parameter is assumed to be known with certainty. Answer: True Reference: Basic Concepts Difficulty: Moderate Keywords: parameter, assumption, certainty The objective function Maximize Z = 3x + 4y is appropriate for linear programming. Answer: False Reference: Basic Concepts Difficulty: Moderate Keywords: linearity, assumption, proportionality 2 2. 3. 4. 5. 6. 199 Copyright ©2010 Pearson Education, Inc. Publishing as Prentice Hall Supplement E • Linear Programming 7. One assumption of linear programming is that...
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...Organization Table 2 Likert five point- scale Unit weight Equivalent weight points Verbal Interpretation 5 4.50-5.0 Strongly Agree 4 3.50-4.49 Agree 3 2.50-3.49 Minimally Agree 2 1.50-2.49 Disagree 1 1.0-1.49 Strongly Disagree Study Habits of CS 1 Students: What do they do outside the classroom? Donald Chinn Institute of Technology University of Washington, Tacoma Tacoma, WA, USA 98402 dchinn@u.washington.edu Judy Sheard Faculty of Information Technology Monash University Victoria, Australia Judy.Sheard@infotech.monash.edu.au Angela Carbone Faculty of Information Technology Monash University Victoria, Australia Angela.Carbone@infotech.monash.edu.au Mikko-Jussi Laakso Department of Information Technology and Turku Centre for Computer Science (TUCS) University of Turku, Finland milaak@utu.fi Abstract In this paper, we report the results of a survey of the study habits of CS1 students. In this survey, students were asked how much time they spent on course-related activities such as reading the textbook, working on problems outside class, using online learning tools, and consulting with their instructor. We identified factors that influenced student study habits and how those factors affected students’ final course score. The findings show that students engaged in a wide range of study behaviours in terms of time spent and use of resources. Previous programming experience and lecture attendance were positive...
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...Linear Programming CHAPTER 6 SUPPLEMENT: Linear Programming Linear Programming is a problem solving approach that has been developed to help managers to make decisions. The following situations describe some typical applications of Linear programming: 1. Selecting a product mix in a factory to make a best use of machine- and labour-hours available while maximizing the firm’s profit. Slides prepared by Romulus Cismaru University of Regina Copyright © 2006 McGraw-Hill Ryerson Limited 6S-1 Copyright © 2006 McGraw-Hill Ryerson Limited 6S-2 Linear Programming some typical applications of Linear programming: Available Hours Product Standard Bag: price $10 (3 hour cutting; 2 hour Sewing ) Deluxe Bag : Price $9 (3 hour cutting; 2 hour Sewing ) How to maximize revenue? Cutting 630 hours Sewing 600 hours 2. Picking blend or raw materials in feed mills to produce finished feed combinations at minimum cost. 3. Determining the distribution that will minimize total shipping cost from several warehouses to various markets locations. 4. A manufacturer wants to develop a production schedule and an inventory policy that will satisfy sales demand in future periods. Copyright © 2006 McGraw-Hill Ryerson Limited 6S-3 Copyright © 2006 McGraw-Hill Ryerson Limited 6S-4 Requirements of Linear Programming Problems 1. LP problems seek to maximize or minimize some quantity (usually profit or cost). We refer to this property as the objective function of...
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...0.1 0.1.1 Linear Programming Objectives By the end of this unit you will be able to: • formulate simple linear programming problems in terms of an objective function to be maximized or minimized subject to a set of constraints. • find feasible solutions for maximization and minimization linear programming problems using the graphical method of solution. • solve maximization linear programming problems using the simplex method. • construct the Dual of a linear programming problem. • solve minimization linear programming problems by maximizing their Dual. 0.1.2 Introduction One of the major applications of linear algebra involving systems of linear equations is in finding the maximum or minimum of some quantity, such as profit or cost. In mathematics the process of finding an extreme value (maximum or minimum) of a quantity (normally called a function) is known as optimization . Linear programming (LP) is a branch of Mathematics which deals with modeling a decision problem and subsequently solving it by mathematical techniques. The problem is presented in a form of a linear function which is to be optimized (i.e maximized or minimized) subject to a set of linear constraints. The function to be optimized is known as the objective function . Linear programming finds many uses in the business and industry, where a decision maker may want to utilize limited available resources in the best possible manner. The limited resources may include material, money, manpower, space...
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... |0 |3 | | | |Applications | | | | | |3 |MC9233 |Software Engineering |3 |0 |0 |3 | |4 |MC9234 |Computer Graphics |3 |0 |0 |3 | |5 |MC9235 |Web Programming |3 |0 |0 |3 | |PRACTICAL | |6 |MC9237 |Graphics Lab |0 |0 |3 |2 | |7 |MC9238 |Microprocessor Lab |0 |0 |3 |2 | |8 |MC9239 |Web Programming Lab |0 |0 |3 |2 | | TOTAL |15 |0 |9 |21 | MC9231 COMPUTER NETWORKS L T P C 3 0 0 3 UNIT I INTRODUCTION 9 Communication model – Data communications...
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...Linear Programming Problems Introduction Linear Programming is one of the most important OR tools in business. It application is universal and helps to save huge amount of money for number of companies. Linear Programming is a deterministic and mathematical programming model. Assumptions of Linear Programming 1) Proportionality: It is assumed that the objective function and constraints increase or decrease proportionally according to the value of decision variables or to the level of activities. 2) Additivity: In linear programming the objective function and the constraints are the total of individual contribution of respective activities. If this is not a reasonable function, we have to assume non- linear model. 3) Divisibility: In Linear Programming it is assumed that the objective functions and constraint expressions are continuous. Integer Programming Model is used where the round off of the decision variable values in Linear Programming solution may not give the optimum integer solution. 4) or Technology coefficient Certainty: In LP the values of each coefficient i.e. Profit, Cost is fixed as a constant. 5) Infinite Choice: In Linear Programming solution there are infinite choices available to decide the level of activities. Formulation of LPP Decision Variables: It is one of the important step in LPP and if defined properly it can convert non-linear problems into linear problems. To define the functions for objectives and constraints...
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...PRINCIPLES OF PROGRAMMING LANGAUAGES Sub Code: IA Marks: Hrs/Week: 04 Exam Hours: 03 Total Hrs: 42 Exam Marks: 100 UNIT I 1. Introduction 4 Hrs Toward higher level languages, Programming paradigms, Language implementation: Bridging the gap, Expression notations, Abstract syntax trees. 2. Types : Data Representation 6 Hrs Elementary data types – Data objects, Variables and Constants, Data types, Declarations, Type checking and type conversion. Numeric data types, Enumerations, Booleans, characters. Structural data types- Structured data objects and data types, Specification of data structure types, Implementation of data structure types, Vectors and arrays, Records, Type equivalence. UNIT II 3. Imperative Programming 6 Hrs Basic statements, Structured sequence control, Handling special cases in loops, Programming with invariants, Proof rules for partial correctness. Procedure activations – simple call-return subprograms, Parameter passing methods, Scope rules for names...
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...LINEAR PROGRAMMING II 1 Linear Programming II: Minimization © 2006 Samuel L. Baker Assignment 11 is on page 16. Introduction A minimization problem minimizes the value of the objective function rather than maximizing it. Minimization problems generally involve finding the least-cost way to meet a set of requirements. Classic example -- feeding farm animals. Animals need: 14 units of nutrient A, 12 units of nutrient B, and 18 units of nutrient C. Learning Objective 1: Recognize problems that linear programming can handle. Linear programming lets you optimize an objective function subject to some constraints. The objective function and constraints are all linear. Two feed grains are available, X and Y. A bag of X has 2 units of A, 1 unit of B, and 1 unit of C. A bag of Y has 1 unit of A, 1 unit of B, and 3 units of C. A bag of X costs $2. A bag of Y costs $4. Minimize the cost of meeting the nutrient requirements. To solve, express the problem in equation form: Cost = 2X + 4Y objective function to be minimized Constraints: 2X + 1Y $ 14 nutrient A requirement 1X + 1Y $ 12 nutrient B requirement 1X + 3Y $ 18 nutrient C requirement 8 8 Read vertically to see how much of each nutrient is in each grain. X $ 0, Y $ 0 non-negativity Learning objective 2: Know the elements of a linear programming problem -- what you need to calculate a solution. The elements are (1) an objective function that shows the cost or profit depending on what choices you make, (2) constraint inequalities...
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...SCHEME OF EXAMINATION FOR MASTER OF COMPUTER APPLICATIONS (MCA) (SIX-SEMESTER Programme) |Semester – I | |Paper |Title of the Paper |Duration |Maximum Marks |Total | |No. | |Of Exam | | | | | | |Theory |Sessional* | | |MCA-101 |Computer Fundamentals and Problem Solving Using C |3 Hours |80 |20 |100 | |MCA-102 |Computer Organisation |3 Hours |80 |20 |100 | |MCA-103 |Discrete Mathematical Structures |3 Hours |80 |20 |100 | |MCA-104 |Software Engineering |3 Hours |80 |20 |100 | |MCA-105 |Computer Oriented Numerical and Statistical Methods |3 Hours |80 |20 |100 | |MCA-106 |Software Laboratory - I |3 Hours | | |100 | | |C (Based on MCA-101) |...
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...d1.1 Object-oriented programming (OOP) is a programming language model organized around "objects" rather than "actions" and data rather than logic. Historically, a program has been viewed as a logical procedure that takes input data, processes it, and produces output data. Object-oriented programming is a programming paradigm that uses abstraction (in the form of classes and objects) to create models based on the real world environment. An object-oriented application uses a collection of objects, which communicate by passing messages to request services. Objects are capable of passing messages, receiving messages, and processing data. The aim of object-oriented programming is to try to increase the flexibility and maintainability of programs. Because programs created using an OO language are modular, they can be easier to develop, and are simpler to understand after development. The characteristics of object oriented programming are as follows: 1. Class A class is a blueprint, or prototype, that defines the variables (data) and the methods (operations) common to all objects of a certain kind. 2. Object Objects are the basic run time entities in an object oriented system. They may represent a person, a, place, a bank account, a table of data or any item that the program has to handle. Objects take up space in memory and have an associated address like record in Pascal, or a structure in C. 3. Encapsulation The act of placing data and the operations that performs...
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...1PGDCA1 1PGDCA2 1PGDCA3 1PGDCA4(A) 1PGDCA4(B) Fundamentals of Computers & Information Technology Introduction to Operating Systems (Dos, Windows, Linux) PC Packages Elective - 1 Foxpro MS-Access 4 4 1 3 T P Theory Paper 80 80 Internal Evaluation 20 20 Practical Exams Total Marks 100 100 4 4 1 3 3 80 80 20 20 25 25 125 125 Semester Total 450 (*L-Lecture, T-Tutorial, P-Practical) SEMESTER –II Subject Code Subject Name Scheme L 2PGDCA1 2PGDCA2 2PGDCA3 2PGDCA4(A) 2PGDCA4(B) 2PGDCA5 System Analysis and Design Programming with Visual Basic.NET Internet & E-Commerce Elective - 2 OOPs & Programming with C++ Financial Accounting with Tally Project Work 4 4 4 4 T 1 P 3 3 3 Theory Paper 80 80 80 80 Internal Evaluation 20 20 20 20 Practical Exams Total Marks 100 125 100 125 25 1 25 4 100 Semester Total 550 General Instructions: 1. For passing the subject examination minimum 40% marks must be separately scored in Theory Paper, Practical Exams and Internal Evaluation in the subject. 2. For passing the semester, minimum aggregate marks must be 45% in the semester. Course : PGDCA Sub Code : 1PGDCA1 Semester: I Subject Name : Fundamentals of Computers & Information Technology Workshops Total Hours Field Visits Practical’s UNIT–I Brief History of Development of Computers, Computer System Concepts, Computer System Characteristics, Capabilities And Limitations, Types...
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...AGGREGATE PLANNING Aggregate planning is intermediate-range capacity planning used to establish employment levels, output rates, inventory levels, subcontracting, and backorders for products that are aggregated, i.e., grouped or brought together. It does not specifically focus on individual products but deals with the products in the aggregate. For example, imagine a paint company that produces blue, brown, and pink paints; the aggregate plan in this case would be expressed as the total amount of the paint without specifying how much of it would be blue, brown or pink. Such an aggregate plan may dictate, for example, the production of 100,000 gallons of paint during an intermediate-range planning horizon, say during the whole year. The plan can later be disaggregated as to how much blue, brown, or pink paint to produce every specific time period, say every month. Achieving a balance of expected supply and demand is the goal of aggregate planning. Informal graphical techniques, as well as mathematical techniques are used by decision makers to handle aggregate planning. Informal Techniques Planners often use graphs or tables to compare current capacity with projected demand requirements. The informal techniques provide some general information and insight but not the specific aggregate production details. The graphs below depict aggregate planning using Level and Chase Strategies. LEVEL STRATEGY Quantity ...
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...Miosha Vogt ET2560 Unit 1 Assignment 1 Chapter 1: Pg. 43 Quick- Check Exercise 1. Machine language 2. Operating System 3. Translation, Linking, Loading, Execution 4. Source 8. Software, Hardware 9. Variables 10. Secondary storage Pg. 44 Review Questions 3. Two secondary storage devices is a disk drive and flash drive Two input devices is the keyboard and mouse Two output devices is the monitor and printer 5. Syntax error is grammar error of a programming language. 6. The loader copies the executed file into memory and initiates execution of instructions. 7. Memory cells are a grouping of small units called bytes Bytes are the amount of storage required to store a single character, composed of even smaller unit called bits. Bits are binary digits 0-10. 8. Three high languages are Fortran, C, and Java FORTRAN used in scientific programming. C is used in system programming. Java supports web programming and programming Android applications. 9. Ram is volatile and it temporarily stores programs while their being executed, delete when computer is turned off, Rom is not volatile the data stored there will not disappear when the computer is turned off. 2. Write an algorithm in pseudo-code to solve the following problem: Input a temperature in Fahrenheit, and output the temperature in Celsius and Kelvin. Formulas needed are: C = ( 59 ) (F – 32). K= ( 59 ) (F – 32) + 273.15 Algorithm: Fahrenheit...
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...Naresh i Technologies Your tiny steps towards programming Programming Languages Arithmetic oriented Languages Assembly Language Machine Language Problem Oriented Languages Pascal ‘C’ WHY YOU SHOULD ADOPT ‘C’ LANGUAGE: General Purpose Language. Structured Programming Language Flexibility towards Systems Programming. Flexibility towards Application Programming. Availability of large number of operators. Has small instruction set. Availability of extensive library function enhancing basic function. Availability for computer of all types. Program highly portable onto multiple platforms. PROGRAM STUCTURE IN ‘C’ It is modular programming called function. Out of all function one should be main (). Components of each function Function Heading: Function Name. 1. List of Arguments. 2. List of Argument Declaration. 3. Compound statements. C programming 1 Fortran Naresh i Technologies SIMPLE REQUIREMENTS OF ‘C’ PROGRAM: Each compound statement should be enclosed in a pair of Braces {}. Braces can contain one or more elementary statements and other compound statements. Compound statements can be nested or individual. Each expression statement must end with a semicolon (;). Comments should be used and can be used anywhere in the program /*…*/ APPROACHES OF LANGUAGES: *Procedural * logical * Artificial Intelligence * Object oriented. CHARACTERISTICS OF A PROGRAM Should...
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...1.1 What is Open source programming? Open-source programming (OSS) is PC programming with its source code made available with a license that helps one to change, explore, and consider diverse methodology. It is made with shared way. The expression "open source" implies something that can be changed or can be shared and accessible successfully to all. [1] "Source code" is the part of programming that most PC customers totally never watch; it's the code PC designers can control to change working and working of programming. Engineers who have permission to a PC program's source code can adjust that program by adding segments to it or settling parts that don't for the most part work honest to goodness. The open-source model is joint headway from various self-sufficient sources, makes an inflexibly more vacillated degree of blueprint. Designer who can access to the item can direct it out to or modify itself so that the customer can interface it easily. [2] 1.2 Difference between open source programming and diverse sorts of programming...
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