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Print Book | 16.00 |
The book covers clear and crisp pedagogy in the field of decision making process, which pervades the activities of every business manager. Modest attempt has been made to discuss some of the commonly used quantitative techniques in a wide spectrum of decision-making situations. It presents the application of various techniques through a large number of examples and review illustrations. A number of problems from various examinations have also been incorporated. Simplicity in explaining complex phenomena and lucidity in style are the twin objectives of the authors in organizing the chapters of the book so that students of Civil, Production, Mechanical, Electrical and Electronics Engineering, Commerce,Management, CA and ICWA can derive maximum benefit.
Prof. Bijoy Kumar Nanda
Professor, Department of Mechanical Engineering, National Institute of Technology, Rourkela
Former Vice Chancellor, Veer Surendra Sai University of Technology, Burla
1. Introduction
Introduction and Historical Development-
Definitions- Applications- Scope- Models in Operations Research- Classifications of Models- Methods of Solving or Models- Steps in or Models- Benefits of or- Limitations of or- Features of or Solutions- or Techniques
2. Linear Programming- Graphical Approach
Introduction- Terms Used in LPP- Advantages of LPP- Limitations of LPP- LP Model Formulation- General Statement in LPP- Assumptions Underlying LPP Model Formulation- Graphical Approach- Maximization Case- Minimization Case- Binding & Non-Binding Constraints- Redundant Constraint- Multiple Optimal Solution- Infeasibility- Unboundedness
3. Linear Programming - Simplex Method
Introduction- Comparison Between Graphical & Simplex Method- Conditions for Simplex Method- Steps for Simplex Method- Slack & Surplus Variables- Maximization Problem- Problem Standardisation- Important Definitions - Initial Basic Feasible Solution(IBFS)- Gauss Elimination Method- Optimum, Degenerate, Nondegenerate Solution- Test for Optimality- Minimization Problem- Artificial Variable Technique(Big M Method)- Two Phase Simplex Method- Dual Simplex Method- Difference Between Simplex & Dual Simplex- Problems On Mixed Constraint, Multiple Optimal Solution, Infeasible Solution, Unbounded Solution, Degeneracy- Methods To Resolve Degenaracy- Shadow Price
4. Duality and Sensitivity Analysis
Introduction- Canonical Form- Standard Form- Primal Dual Relationship- Structural Similarity- Sensitivity Analysis- Post Optimality Analysis- Parametric Programming- Change in Coefficients of Nonbasic Variables in Objective Function- Change in Coefficients of Basic Variables in Objective Function- Change in RHS Constraints- Change in Technological Coefficients Of Nonbasic Variables- Addition of New Constraint
5. Transportation Problem
Introduction- Transportation Model- Important Definitions - Feasible Solution- Basic Feasible Solution- Nondegenerate Basic Feasible Solution- Optimal Solution- North West Corner Rule- Least Cost Method or Matrix Minima Method- Vogel’s Approximation Method (Vam) - Stepping Stone Method- Modified Distribution Method (Modi)- Unbalanced Transportation Problem- Maximization in Transportation Problem- Degeneracy in Transportation Problem
6. Assignment Problem
Introduction- Difference Between Transportation & Assignment Model- Hungarian Method- Unbalanced Assignment Problem- Maximization in Assignment Problem- Prohibited Assignment- Travelling Salesman Problem
7. Sequencing Problem
Introduction- Terminology- Assumptions- N Jobs Thru’ 2 Machines- Gantt Charts- Johnson's Rule- N Jobs Thru’ 3 Machines- N Jobs Thru’ K Machines- 2 Jobs Thru’ K Machines- Graphical Solution
8. Decision Theory
Introduction- What is Decision- Two Phases of Decision Making- Steps in Decision Making- Characteristics of Decision Making- Decision Making Circumstances- Terminology- Decision Under Uncertainity- Maximax, Maximin, Minimax, Minimin, Laplace, Hurwicz Criteria, Savage Criteria- Decision Under Risk- Emv- Eol- Evpi- Eppi- Decision Tree- Roll Back Process- Advantages & Limitations of Tree Approach
9. Game Theory
Introduction- Classifications- Pure & Mixed Strategy- Two Person Zero Sum Game- Saddle Point- Dominance Rule- Subgame Method- Graphical Method- Iterative Method of Approximate Solution- Linear Programming Approach
10. Simulation
Introduction- Classifications- Advantages- Limitations- Monte Carlo Simulation Technique- Generation of Random Numbers
11. Queueing Theory
Introduction- Historical Development- Input Source- Queue- Service Discipline- Service Mechanism- System Output- Customer Behaviour- Terminology- Steady, Transient and Explosive States- Distributions of Arrival and Service Time- Single Server Poisson Arrival With Exponential Service Infinite Population- Cost Analysis- (M/M/C): Gd / - /- Multi Channel Queueing Theory- (M/M/1): Gd/M/- (M/Ek/1): Fcfs / - / - Poisson Input & Constant Service Time
12. CPM / Pert
Introduction- Why Pert/CPM- Characteristics Of Pert/CPM- Terminology- Network Construction- Estimation Of Activity Time- Probability of Achieving Completion Data- Time Cost Relationship (Crashing)- Time Cost Optimization- CPM Updating- Resource Allocation- Resource Levelling- Resource Smoothing
13. Inventory Control
Introduction- Classification- Why Inventory- Advantages- Factors in Inventory Control- Costs Involved in Inventory- Systems in Inventory Control- P, Q, Pq, Abc, Xyz, Ved, Sde, Hml, Nmg, Fnsd Analysis- Economic Order Quantity- Functions- Inventory Level- Inventory Models- Eoq With Uniform Demand- Eoq With Several Production Runs Of Unequal Length- Eoq With Non instantaneous Stock Replenishment - Stock Outs- Eoq With Instantaneous Production And Variable Order Cycle- Eoq With Instantaneous Production & Fixed Order Cycle- Eoq With Gradual Supply & Shortages Allowed- Eoq With Price Breaks- Eoq With More Than One Price Break- Reordering Systems- Buffer Stock And Reordering Level- Periodic Inventory Ordering System- Two Bin System
14. Integer Programming
Introduction- Cutting Plane Algorithm- Gomory’s Fractional Cut- Branch & Bound Method
Selected References
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