UNIQUE SERIES AKTU Syllabus
BOE075

Operations Research

L-T-P3-0-0 Credits3 Session2025-26 TypeTheory
Appears in 36 semesters · 36 branches

B.Tech Civil Engineering · Sem 7 (Open Elective-II) · B.Tech Mechanical Engineering · Sem 7 (Open Elective-II) · B.Tech Computer Science & Engineering · Sem 7 (Open Elective-II) · B.Tech Information Technology · Sem 7 (Open Elective-II) · B.Tech Artificial Intelligence & Machine Learning · Sem 7 (Open Elective-II) · B.Tech Artificial Intelligence & Data Science · Sem 7 (Open Elective-II) · B.Tech CSE (Artificial Intelligence) · Sem 7 (Open Elective-II) · B.Tech CSE (AI & ML) · Sem 7 (Open Elective-II) · B.Tech CSE (Data Science) · Sem 7 (Open Elective-II) · B.Tech CSE (Cyber Security) · Sem 7 (Open Elective-II) · B.Tech CSE (Internet of Things) · Sem 7 (Open Elective-II) · B.Tech Computer Science & Design · Sem 7 (Open Elective-II) · B.Tech Computer Science (Hindi) · Sem 7 (Open Elective-II) · B.Tech Computer Science & Business Systems · Sem 7 (Open Elective-II) · B.Tech Electrical Engineering · Sem 7 (Open Elective-II) · B.Tech Electrical & Electronics Engineering · Sem 7 (Open Elective-II) · B.Tech Electrical & Computer Engineering · Sem 7 (Open Elective-II) · B.Tech Electronics & Communication Engineering · Sem 7 (Open Elective-II) · B.Tech Electronics & Instrumentation / Instrumentation & Control · Sem 7 (Open Elective-II) · B.Tech Electronics & Computer Engineering · Sem 7 (Open Elective-II) · B.Tech ECE (Advanced Communication Technology) · Sem 7 (Open Elective-II) · B.Tech Electronics Engineering (VLSI Design & Technology) · Sem 7 (Open Elective-II) · B.Tech Automobile Engineering · Sem 7 (Open Elective-II) · B.Tech Aeronautical Engineering · Sem 7 (Open Elective-II) · B.Tech Mechanical & Industrial Engineering · Sem 7 (Open Elective-II) · B.Tech Production & Industrial Production Engineering · Sem 7 (Open Elective-II) · B.Tech Manufacturing Technology · Sem 7 (Open Elective-II) · B.Tech Mining Engineering · Sem 7 (Open Elective-II) · B.Tech Chemical Engineering · Sem 7 (Open Elective-II) · B.Tech Plastic Engineering · Sem 7 (Open Elective-II) · B.Tech Food Technology · Sem 7 (Open Elective-II) · B.Tech Textile Technology · Sem 7 (Open Elective-II) · B.Tech Handloom & Textile Technology · Sem 7 (Open Elective-II) · B.Tech Carpet & Textile Technology · Sem 7 (Open Elective-II) · B.Tech Biotechnology · Sem 7 (Open Elective-II) · B.Tech Agricultural Engineering · Sem 7 (Open Elective-II)

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Syllabus

5 units · 40 lecture hours
Unit1

Unit 1: Introduction

8 hrs

Definition and scope of operations research (OR), OR model, solving the OR model, art of modelling, phases of OR study. Linear Programming: Two variable Linear Programming model and Graphical method of solution, Simplex method, Dual Simplex method, special cases of Linear Programming, duality, sensitivity analysis.

Unit2

Unit 2: Transportation Problems

8 hrs

Types of transportation problems, mathematical models, transportation algorithms, Assignment: Allocation and assignment problems and models, processing of job through machines.

Unit3

Unit 3: Network Techniques

8 hrs

Shortest path model, minimum spanning Tree Problem, Max-Flow problem and Min-cost problem. Project Management: Phases of project management, guidelines for network construction, CPM and PERT

Unit4

Unit 4: Theory of Games

8 hrs

Rectangular games, Minimax theorem, graphical solution of 2x n or mx2 games, game with mixed strategies, reduction to linear programming model. Quality Systems: Elements of Queuing model, generalized Poisson queing model, single server models.

Unit5

Unit 5: Inventory Control

8 hrs

Models of inventory, operation of inventory system, quantity discount. Replacement: Replacement models: Equipment’s that deteriorate with time, equipment’s that fail with time.

Course Objectives1 points
  • The objective of this course is to provide a comprehensive understanding of core machine learning concepts, algorithms, and models, enabling students to design, implement, and evaluate learning systems across various paradigms including neural networks, Bayesian methods, and reinforcement learning.
Course Outcomes (COs)5 outcomes

After completion of the course student will be able to:

  1. CO1Understand the scope, phases, and modeling techniques of Operations Research and apply linear programming methods, including simplex and dual simplex, to solve optimization problems.K2
  2. CO2Formulate and solve transportation and assignment problems using appropriate mathematical models and algorithms.K2
  3. CO3Apply network techniques like shortest path, minimum spanning tree, max-flow, and CPM/PERT for efficient project and resource management.K3
  4. CO4Analyze decision-making problems using game theory and queuing models, and evaluate their practical applications in operations systems.K4
  5. CO5Apply inventory and replacement models for effective control of stock and maintenance of deteriorating or failing equipment.K3

Text Books

  1. Wayne L. Winston, “Operations Research” Thomson Learning, 2003.
  2. Hamdy H. Taha, “Operations Research-An Introduction” Pearson Education, 2003.
  3. R. Panneer Seevam, “Operations Research” PHI Learning, 2008.
  4. V. K. Khanna, “Total Quality Management” New Age International, 2008.

Official AKTU syllabus

This subject is on page 13, 14 of the original AKTU PDF.

Official AKTU syllabus PDF ↗