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Previous year question paper for AOR (MBA 3rd)

Applied operations research

Previous year question paper with solutions for applied operations research from 2008 to 2019.

Our website provides solved previous year question paper for Applied operations research from 2008 to 2019. Doing preparation from the previous year question paper helps you to get good marks in exams. From our AOR question paper bank, students can download solved previous year question paper. The solutions to these previous year question paper are very easy to understand.

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Operations Research

Dive into ‘Operations Research’ to master the art of problem-solving and decision-making in complex business environments. Learn about optimization techniques, statistical analysis, and mathematical modeling. Understand how to apply these tools to enhance operational efficiency and strategic planning in various business scenarios.

1 Operations Research-An Overview

• History of O.R.
• Approach, Techniques and Tools
• Phases and Processes of O.R. Study
• Typical Applications of O.R
• Limitations of Operations Research
• Models in Operations Research
• O.R. in real world

2 Linear Programming: Formulation and Graphical Method

General formulation of Linear Programming Problem

• Optimisation Models
• Basics of Graphic Method
• Important steps to draw graph
• Multiple, Unbounded Solution and Infeasible Problems
• Solving Linear Programming Graphically Using Computer
• Application of Linear Programming in Business and Industry

3 Linear Programming-Simplex Method

• Principle of Simplex Method
• Computational aspect of Simplex Method
• Simplex Method with several Decision Variables
• Two Phase and M-method
• Multiple Solution, Unbounded Solution and Infeasible Problem
• Sensitivity Analysis
• Dual Linear Programming Problem

4 Transportation Problem

• Basic Feasible Solution of a Transportation Problem
• Modified Distribution Method

Stepping Stone Method

• Unbalanced Transportation Problem
• Degenerate Transportation Problem
• Transhipment Problem
• Maximisation in a Transportation Problem

5 Assignment Problem

• Solution of the Assignment Problem
• Unbalanced Assignment Problem
• Problem with some Infeasible Assignments
• Maximisation in an Assignment Problem
• Crew Assignment Problem

6 Application of Excel Solver to Solve LPP

• Building Excel model for solving LP: An Illustrative Example

7 Goal Programming

• Concepts of goal programming
• Goal programming model formulation

Graphical method of goal programming

• The simplex method of goal programming

Using Excel Solver to Solve Goal Programming Models

• Application areas of goal programming

8 Integer Programming

• Some Integer Programming Formulation Techniques
• Binary Representation of General Integer Variables
• Unimodularity
• Cutting Plane Method
• Branch and Bound Method
• Solver Solution

9 Dynamic Programming

Dynamic Programming Methodology: An Example

• Definitions and Notations

Dynamic Programming Applications

10 Non-Linear Programming

• Solution of a Non-linear Programming Problem
• Convex and Concave Functions
• Kuhn-Tucker Conditions for Constrained Optimisation
• Quadratic Programming
• Separable Programming
• NLP Models with Solver

11 Introduction to game theory and its Applications

• Important terms in Game Theory
• Saddle points
• Mixed strategies: Games without saddle points
• 2 x n games
• Exploiting an opponent’s mistakes

12 Monte Carlo Simulation

• Reasons for using simulation
• Monte Carlo simulation
• Limitations of simulation
• Steps in the simulation process
• Some practical applications of simulation
• Two typical examples of hand-computed simulation
• Computer simulation

13 Queueing Models

• Characteristics of a queueing model
• Notations and Symbols
• Statistical methods in queueing
• The M/M/I System
• The M/M/C System
• The M/Ek/I System
• Decision problems in queueing

Syllabus with topics linked

The Evolution of Operations Research: From Military Strategy to Business Management

Discover the history of Operations Research (OR) and how it evolved from a military strategy tool to a valuable decision-making tool in business and government. Learn more in this informative blog.

Approach, Techniques, and Tools of Operations Research: A Comprehensive Guide

Learn about the approach, techniques, and tools used in operations research to optimize resources and solve complex problems. Discover how mathematical models, simulation software, and statistical software aid decision-making.

Understanding Phases and Processes of Operations Research (O.R.) Study

Discover the different phases and processes of Operations Research (O.R.) study, including problem definition, data collection, model construction, and implementation in this comprehensive blog.

Typical Applications of Operations Research: Examples and Benefits

Discover typical applications of Operations Research (O.R.), an interdisciplinary field that helps organizations make better decisions by using mathematical modeling and optimization techniques. Learn how O.R. can be used in inventory management, production planning, supply chain management, transportation and logistics, healthcare, and finance.

Understanding the Limitations of Operations Research

This informative blog talks about limitations of operations research.

Models in Operations Research: A Comprehensive Guide to Understand and Apply OR Models

Learn about the different types of models used in Operations Research, their advantages and limitations, and how they are applied in real-world scenarios.

Operations Research in Real World: Making Data-Driven Decisions

Discover the real-world applications of Operations Research and how it helps businesses make data-driven decisions. Learn how it can improve your problem-solving skills.

Learn about the general formulation of a linear programming problem and the role of the objective function, decision variables, and constraints in optimizing a linear relationship.

Optimisation Models: Techniques and Applications for Efficient Decision Making

Optimization models are a set of techniques and tools used to improve decision-making processes by finding the best possible solution for a problem. These models help managers and decision-makers allocate resources, plan operations, and manage inventory effectively....

Basics of Graphic Method: Understanding Linear Programming Graphical Solution

Learn the basics of graphic method and steps to solve linear programming problems with a visual representation of the problem on a graph.

Important Steps to Draw Graph: A Comprehensive Guide

Learn the important steps to draw a graph for a linear programming problem.

Multiple, Unbounded, and Infeasible Problems in Linear Programming

Learn about multiple, unbounded, and infeasible problems in linear programming, including how to identify and handle these scenarios in your optimization models.

Solving Linear Programming Graphically Using Computer: Step-by-Step Guide

Learn how to solve linear programming problems graphically using a computer in this step-by-step guide. Formulate the problem, plot the constraints and objective function, and interpret the results.

Real World Applications of Linear Programming

Discover the various applications of linear programming in business and industry, including production planning, transportation, resource allocation, and more, to optimize decision-making and increase profitability.

Understanding the Principle of Simplex Method in Linear Programming

Learn the Principle of Simplex Method in Operations Research with this step-by-step guide. Understand and apply it to solve real-world problems for optimal solutions.

Understanding the Computational Aspect of Simplex Method

Learn the computational aspect of Simplex Method for solving Linear Programming Problems, how to implement it using a computer program, and its efficiency.

Simplex Method with Several Decision Variables: Optimizing Complex Problems

Learn how the simplex method with several decision variables is used to optimize complex problems in operations research. Discover the phases, computational aspects, and practical applications in this informative blog.

Two Phase and M-Method in Linear Programming: An Overview

Want to learn more about Two Phase and M-Method in Linear Programming? This blog provides a comprehensive guide on their definitions, applications, and limitations.

Multiple, Unbounded, and Infeasible Solutions in Linear Programming

Learn about multiple, unbounded, and infeasible solutions in linear programming. Explore how to identify and interpret these concepts to make more informed decisions.

Sensitivity Analysis in Linear Programming: Understanding and Interpreting Results

Learn about sensitivity analysis in linear programming and how it helps to interpret the impact of small changes on the optimal solution. Understand how to use shadow prices and allowable changes to make informed decisions.

Understanding the Dual Linear Programming Problem: A Comprehensive Guide

Learn about the dual linear programming problem in this comprehensive guide. Understand how it works, why it’s important, and how to use it to verify optimal solutions.

Basic Feasible Solution of a Transportation Problem: Understanding the Key Concepts

Learn about Basic Feasible Solution of a Transportation Problem, the starting point for finding the optimal solution for transporting goods in a cost-effective way. Discover the North-West Corner Rule and other methods used to find the basic feasible solution.

Modified Distribution Method: Solving Transportation Problems

Learn how Modified Distribution Method can help you solve transportation problems easily. Follow our step-by-step guide to understand the technique and its advantages.

Learn how the Stepping Stone Method can help you optimize transportation problems. Our comprehensive guide covers its definition, steps, and application in Operations Research.

Understanding Unbalanced Transportation Problem: Definition, Methods, and Applications

Learn about the Unbalanced Transportation Problem: its definition, methods, and applications. Discover how this special case of the transportation problem can help solve inventory and transportation issues.

Understanding the Degenerate Transportation Problem: Causes, Consequences, and Solutions

Learn about the causes, consequences, and solutions to the Degenerate Transportation Problem in this informative blog. Discover how to address degeneracy in transportation problems.

Transhipment Problem: Solving Complex Logistics Challenges

Learn about the Transhipment Problem in Operations Research, an important concept that deals with optimizing transportation costs. Explore its applications and how to solve it with linear programming techniques.

Maximisation in a Transportation Problem: Formulation, Methods and Applications

Learn about maximisation in a transportation problem, including its formulation, methods, and applications in logistics and supply chain management. Optimize your resource allocation and improve your supply chain efficiency.

How to Solve the Assignment Problem: A Complete Guide

Solve the assignment problem with ease using the Hungarian method. Our comprehensive guide walks you through the steps to minimize costs and maximize profits.

Unbalanced Assignment Problem: Definition, Formulation, and Solution Methods

Learn about the Unbalanced Assignment Problem in Operations Research (OR) – its definition, formulation, and solutions. Solve assignment problems with ease!

Understanding the Problem with Some Infeasible Assignments in Assignment Models

Learn about infeasible assignments in assignment models, why they occur, and how to deal with them in this informative blog. Ensure your decision-making is not compromised.

Maximisation in an Assignment Problem: Optimizing Assignments for Maximum Benefit

Learn how to maximize the benefits associated with each task in an assignment problem. This blog covers everything from understanding the problem to implementing solutions.

Crew Assignment Problem: Optimizing the Allocation of Tasks to Crew Members

Learn about Crew Assignment Problem and how it helps optimize the allocation of tasks to crew members. Explore its benefits, challenges, and real-world applications.

Building Excel Model for Solving LP: An Illustrative Example

Learn how to solve Linear Programming problems in Excel by building an Excel model. Follow a step-by-step approach using an illustrative example of a company producing two products.

Understanding the Concepts of Goal Programming

Learn about the concepts of goal programming, its advantages, and how it can be applied in real-world scenarios. Discover a powerful technique that can help you solve problems with multiple conflicting objectives.

Goal Programming Model Formulation: An Overview

Are you looking for a way to balance multiple objectives in your decision-making process? Look no further than goal programming! In this blog, we'll explore the basics of goal programming model formulation, including its concepts, methodology, and applications....

Learn how to solve complex decision-making problems using the graphical method of goal programming. Discover how this approach provides a visual representation of the feasible solution space and helps identify the optimal solution.

The Simplex Method of Goal Programming: Formulation, Steps, and Applications

Learn how to solve multi-objective problems using the powerful simplex method of goal programming. Follow our step-by-step guide to apply the technique to a wide range of optimization problems.

Learn how to solve goal programming models using Excel Solver with our comprehensive guide. Get step-by-step instructions for setting up your spreadsheet, defining your objective functions, and analyzing your results.

Application Areas of Goal Programming: An Overview

Discover the application areas of goal programming in this comprehensive guide. Learn how goal programming can be used to optimize multiple goals simultaneously in engineering, finance, healthcare, environmental management, and supply chain management.

Some Integer Programming Formulation Techniques: A Guide to Optimizing Integer Solutions

Learn about Some Integer Programming Formulation Techniques and how they can help you find the best integer solutions for your problems. Discover powerful tools like branch and bound method, cutting plane method, unimodularity, and binary representation of general integer variables.

Binary Representation of General Integer Variables: An Introduction

Learn about binary representation of general integer variables and how it is used in computer science and operations research. Find out how it allows us to solve integer programming problems in logistics, scheduling, and network optimization.

Unimodularity: Understanding the Concept and its Significance in Integer Programming

Learn about unimodularity in Integer Programming and how it simplifies problem-solving. Explore the properties and applications of unimodular matrices in this informative blog.

Cutting Plane Method: An Optimization Technique for Integer Programming

Learn about the Cutting Plane Method, an optimization technique used to solve complex Integer Programming problems. Explore its applications and benefits in real-world scenarios.

Branch and Bound Method: An Efficient Algorithm for Solving Integer Programming Problems

Learn about the Branch and Bound Method for solving integer programming problems. Find out how it works, when to use it, and its benefits. Get expert insights in our informative blog.

Understanding Solver Solution: An Overview of Operations Research Technique

Learn how Solver Solution, an add-in tool in Excel, can help you optimize complex problems and make better decisions. Solve linear, nonlinear, integer, and mixed-integer programming problems with ease.

Learn about Dynamic Programming Methodology through a step-by-step example of finding the shortest path between two points in a grid. Break down complex problems, store solutions, and solve even the most challenging problems with ease.

Understanding Definitions and Notations in Operations Research

Learn the importance of Definitions and Notations in Operations Research. Explore the common terminologies, variables and constraints used in O.R. models in this informative blog.

Learn about the powerful problem-solving technique of dynamic programming and its many applications across fields such as operations research, computer science, economics, and engineering. Find optimal solutions that take into account constraints such as resource availability, time, and cost.

Non-Linear Programming: Techniques for Finding Optimal Solutions

Learn about the techniques and applications of Non-Linear Programming (NLP) in this informative blog. Discover how to optimize complex systems with convex and concave functions, Kuhn-Tucker conditions for constrained optimization, quadratic programming, separable programming, and more.

Convex and Concave Functions: Understanding the Difference and Their Applications

Learn the difference between convex and concave functions and their applications in operations research. Examples and explanations provided in this informative blog.

Kuhn-Tucker Conditions for Constrained Optimisation: Understanding the Basics

Learn how Kuhn-Tucker conditions work in constrained optimization problems. Understand the basics and advantages of using these powerful mathematical tools to solve non-linear optimization problems.

Quadratic Programming: Optimizing Non-Linear Problems with Precision

Learn about Quadratic Programming, a powerful optimization technique used to solve non-linear programming problems with precision. Discover its applications and advantages in finance, engineering, and computer science.

Separable Programming: An Introduction to Solving Complex Optimization Problems

Learn how Separable Programming can help solve complex optimization problems more efficiently & effectively. This blog provides an introduction to Separable Programming.

NLP Models with Solver: Solving Complex Optimization Problems

Learn how NLP models with Solver can help you solve complex optimization problems quickly and easily. Explore the benefits of NLP models and how to set up and run an NLP model in Excel with Solver.

Important Terms in Game Theory: Understanding the Basics

Learn the essential concepts of game theory with our comprehensive guide on important terms in game theory. Understand Nash equilibrium, dominant strategy, and more!

Saddle Points: Understanding the Concept and its Applications in Game Theory

Learn about saddle points in game theory and how they represent a type of equilibrium that is more stable than other types of equilibria. Find examples and more in this informative blog.

Learn about dominance in game theory and how it is used to eliminate strategies, predict outcomes, find Nash Equilibrium, and solve games. Simplify complex games by understanding the concept of dominance.

Mixed Strategies: Understanding Games without Saddle Points

Learn how mixed strategies can be used to approach games without saddle points. Understand the concept of mixed strategies and the importance of using them to level the playing field in game theory.

Understanding 2 x n Games: Strategies and Applications

Learn about 2 x n games in game theory. This blog explains what they are, how they work, and their applications in various fields, including economics, political science, and computer science.

Exploiting an Opponent’s Mistakes: How to Gain an Advantage in Game Theory

Learn how to exploit your opponent’s mistakes and gain an advantage in game theory. Discover effective strategies for recognizing and capitalizing on your adversary’s errors.

Reasons for Using Simulation: Exploring the Benefits of this Powerful Analytical Tool

Discover the reasons why simulation is a powerful analytical tool that can help organizations make informed decisions, optimize processes, and predict outcomes. Learn more in this informative blog.

Monte Carlo Simulation: An Introduction to the Method

Learn the basics of Monte Carlo simulation and how it is used in operations research. This blog covers the method’s steps, limitations, and practical applications.

Limitations of Simulation: Understanding the Challenges in Modeling Real-World Systems

Discover the key limitations of simulation in Operations Research and how they impact decision making in business and industry.

Steps in the Simulation Process: A Comprehensive Guide

Learn about the Steps in the Simulation Process and how it helps to evaluate the system’s performance accurately. Read this comprehensive guide to get insights.

Some Practical Applications of Simulation: Understanding its Uses and Benefits

Explore the practical applications of simulation in different industries, including healthcare, manufacturing, transportation, and defense. Learn how simulation is used to improve decision-making and identify potential problems.

Two Typical Examples of Hand-Computed Simulation: Understanding the Basics

Learn about two typical examples of hand-computed simulation with this informative blog. Understand how this method works, and explore its limitations.

Computer Simulation: Understanding Its Importance and Applications

Learn about the importance and applications of computer simulation. Explore how it helps model complex systems, predict their behavior and analyze their performance.

Understanding the Characteristics of a Queueing Model: A Beginner’s Guide

Learn about the fundamental characteristics of a queueing model in this beginner’s guide. Discover how queueing models optimize performance in various industries.

Notations and Symbols in Queuing Model: Understanding the Basics

Learn the notations and symbols used in Queuing Models, which play a crucial role in analyzing and optimizing the performance of waiting line systems.

Statistical Methods in Queueing: Analyzing and Optimizing Customer Service

Learn about statistical methods in queueing and how to optimize the flow of customers in a service system. Explore queueing models, decision problems in queueing, and more in this informative blog.

Understanding the M/M/I System in Queueing Theory

Learn about the M/M/I system in queueing theory and gain a comprehensive understanding of its key components, characteristics, and applications.

Understanding The M/M/C System: An Overview of Queuing Models

Learn about the M/M/C system, a fundamental queuing model used to analyze waiting lines and customer service processes. Explore characteristics, applications, and how to solve it.

The M/Ek/I System: Understanding the Notations, Characteristics and Decision Problems

Learn about the M/Ek/I system in Operations Research, including its notations, characteristics, and decision problems. Understand how to apply it in real-world situations.

Decision Problems in Queueing: Understanding the Complexities of Waiting Lines

Learn how decision problems in queueing use statistical methods and optimization techniques to optimize system performance in real-world scenarios.

Operation Research Notes | PDF, Syllabus | MBA, B Tech 2024

• Post last modified: 5 April 2022
• Reading time: 37 mins read
• Post category: MBA Study Material / B Tech Study Material / BBA Study Material / BCOM Study Material

Download Operation Research Notes , books, syllabus PDF for MBA, BBA, B.COM 2024. We provide complete operation research pdf . Business law lecture notes include operation research notes , operation research book, courses, case study, syllabus , question paper, MCQ, questions and answers and available in operation research pdf form.

Operation Research subject is included in MBA 1st semester subjects, business legislation MBA notes, Operation Research B Tech Notes, BBCOM 1st sem subjects and operation research BBA notes. So students can able to download operation research notes for MBA 1st sem pdf

Table of Content

• 1 Operation Research Syllabus
• 2 Operating Systems PDF
• 3 Operation Research Note
• 4 Operation Research Questions and Answers
• 5 Operation Research Question Paper
• 6 Operation Research Book
• 7 Go On, Share & Help your Friend

Operation research Notes can be downloaded in operation research pdf from the below article.

Operation Research Syllabus

A detailed Operation Research Syllabus as prescribed by various Universities and colleges in India are as under. You can download the syllabus in operation research pdf form.

Unit 1 – Introduction to Operations Research: Introduction, Historical Background, Scope of Operations Research, Features of Operations Research, Phases of Operations Research, Types of Operations Research Models, Operations Research Methodology, Operations Research Techniques and Tools, Structure of the Mathematical Model, Limitations of Operations Research

Unit 2 – Linear Programming: Introduction, Linear Programming Problem, Requirements of LPP, Mathematical Formulation of LPP,    Case Studies of LPP, Graphical Methods to Solve Linear Programming Problems, Applications, Advantages, Limitations

Unit 3 – Graphical Analysis of Linear Programming Problems: Introduction, Graphical Analysis, Some Basic Definitions, Graphical Methods to Solve LPP, Some Exceptional Cases, Important Geometric Properties of LPP

Unit 4 – Simplex Method: Introduction, Standard Form of LPP, Fundamental theorem of LPP, Solution of LPP – Simplex Method, The Simplex Algorithm, Penalty Cost Method or Big M-method, Two-Phase Method, Solved Problems on Minimisation

Unit 5   -Duality in Linear Programming Problem: Introduction, Importance of Duality Concepts, Formulation of Dual Problem, Economic Interpretation of Duality, Sensitivity Analysis

Unit 6   -Transportation Problem: Introduction, Formulation of Transportation Problem (TP), Transportation Algorithm (MODI Method), the Initial Basic Feasible Solution, Moving Towards Optimality

Unit 7 – Assignment Problem: Introduction, Mathematical Formulation of the Problem, Hungarian Method Algorithm, Routing Problem, Travelling Salesman Problem

Unit 8 – Integer Programming Problem: Introduction, Types of Integer Programming Problems, Gomory’s All-IPP Method, All IPP Algorithm, Branch and Bound Technique

Unit 9   -Infinite Queuing Models: Introduction, Queuing Theory, Operating Characteristics of a Queuing System, Constituents of a Queuing System, Service Facility, Queue Discipline

Unit 10 -Mathematical Analysis of Queuing Theory: Introduction, Mathematical Analysis of Queuing Process, Properties of Queuing System, Notations, Service System, Single Channel Models, Multiple Service Channels, Erlang Family of Distribution of Service Times, Applications of Queuing Theory, Limitations of Queuing Theory

Unit 11 – Finite Queuing Models: Introduction, Finite Queuing Models

Unit 12 – Simulation: Introduction, Methodology of Simulation, Basic Concepts, Simulation Procedure, Application of Simulation

Unit 13 – Simulation Monte-Carlo Method: Introduction, Monte-Carlo Simulation, Applications of Simulation, Advantages of Simulation, Limitations of Simulation

Unit 14 – Project Scheduling and PERT-CPM: Introduction, Basic Difference between PERT and CPM, PERT/CPM Network Components and Precedence Relationship, Project Management – PERT

Unit 15 – Game Theory: Introduction, Competitive Situations, Characteristics of Competitive Games, Maximin – Minimax Principle, Dominance

Operating Systems PDF

Operation research note.

What is Operation Research?

Operations research (British English: operational research) (OR) is a discipline that deals with the application of advanced analytical methods to help make better decisions.

Further, the term operational analysis is used in the British (and some British Commonwealth) military as an intrinsic part of capability development, management and assurance. In particular, operational analysis forms part of the Combined Operational Effectiveness and Investment Appraisals, which support British defence capability acquisition decision-making.

Operation Research Questions and Answers

Some of the operation research questions and answers are mentioned below. You can download the QnA in operation research pdf form.

• Define Operations Research.
• What are the assumptions of LPP?
• What is Degeneracy in Transportation?
• Define prohibited assignment problems.
• Illustrate Saddle point.
• What is sequencing problem?
• Define the concept of EOQ.
• Differentiate between PERT and CPM.
• How to compute Re-order level of inventory?
• What is Duality?

Operation Research Question Paper

If you have already studied the operation research notes, then its time to move ahead and go through previous year operation research question paper.

It will help you to understand question paper pattern and type of operation research questions and answers asked in MBA, BBA, BCom operation research exam. You can download the syllabus in operation research pdf form.

Operation Research Book

Below is the list of operation Research Book recommended by the top university in India.

• Hamdy A Taha, 1999. Introduction to Operations Research, PHI Limited, New Delhi.
• Sharma, J.K., 1989. Mathematical Models in Operations Research, TMH
• Beer, Stafford, 1966. Decision and Control, John Wiley & Sons, New York.
• Levin, Rubin, Stinson, Gardner, 1992. Quantitative Approaches to Management, TMH
• Wagner, Harvery M., 1975. Principles of Operations Research, PHI, Egnlewood Cliffs, N.J.

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Principles of Management Notes ✅ PDF

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Operation Research Notes ✅ PDF

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Operations Research

1. Operations Research approach is ______________.

• multi-disciplinary
• collect essential data

2. A feasible solution to a linear programming problem ______________.

• must satisfy all the constraints of the problem simultaneously
• need not satisfy all of the constraints, only some of them
• must be a corner point of the feasible region.
• must optimize the value of the objective function

3. If any value in XB column of final simplex table is negative, then the solution is ______________.

• no solution

4. For any primal problem and its dual______________.

• optimal value of objective function is same
• dual will have an optimal solution iff primal does too
• primal will have an optimal solution iff dual does too
• both primal and dual cannot be infeasible

5. The difference between total float and head event slack is ______________

• independent float
• interference float
• linear float

6. An optimal assignment requires that the maximum number of lines which can be drawn through squares with zero opportunity cost should be equal to the number of ______________.

• rows or columns
• rows and columns.
• rows+columns- 1
• rows-columns.

7. To proceed with the Modified Distribution method algorithm for solving an transportation problem, the number of dummy allocations need to be added are______________.

8. Select the correct statement

• EOQ is that quantity at which price paid by the buyer is minimum
• If annual demand doubles with all other parameters remaining constant, the Economic Order Quantity is doubled
• Total ordering cost equals holding cost
• Stock out cost is never permitted

9. Service mechanism in a queuing system is characterized by ______________.

• customers behavior
• servers behavior
• customers in the system
• server in the system

10. The objective of network analysis is to______________.

• minimize total project duration
• minimize toal project cost
• minimize production delays, interruption and conflicts
• maximize total project duration

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