Why enroll

Participants join this course to develop a structured, analytical approach to solving complex decision-making problems involving limited resources and competing objectives. The course equips learners with proven optimization and modeling techniques that are widely used in engineering, operations management, logistics, finance, and analytics-driven roles.

By joining, participants gain practical skills in formulating real-world problems into mathematical models, applying quantitative methods to identify optimal solutions, and interpreting results for effective managerial and technical decisions. The course strengthens problem-solving capability, improves logical and quantitative reasoning, and provides a strong foundation for advanced studies or professional applications in optimization, systems analysis, and data-driven decision support.

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Course content

The course is readily available, allowing learners to start and complete it at their own pace.

Fundamentals of operation research

22 Lectures

1233 min

Introduction to Linear Programming Formulations
Preview
51 min
Linear Programming Formulations (Contd...)
52 min
Linear Programming Solutions- Graphical Methods
52 min
Linear Programming Solutions - Simplex Algorithm
51 min
Simplex Algorithm-Minimization Problems
52 min
Simplex Algorithm - Initialization and Iteration
52 min
Simplex Algorithm - Termination
51 min
Introduction to Duality
51 min
Primal Dual Relationships, Duality Theorems
51 min
Dual Variables and the Simplex Tables
51 min
Simplex Algorithm in Matrix Form - Sensitivity Analysis
61 min
Sensitivity Analysis Transportation Problem (Intro...)
61 min
Transportation Problems
60 min
Transportation Problem-Optimal Solutions
61 min
Transportation Problem-Other Issues
61 min
Assignment Problem - Hungarian Algorithm
60 min
Other Issues - Introduction to Dynamic Programming
61 min
Dynamic Programming - Involving Discrete Variables
54 min
Dynamic Programming - Continuous Variables
59 min
Dynamic Programming - Linear and Integer Problems
60 min
Inventory Models - Deterministic Models
61 min
Inventory Models - Discount Models
60 min

Course details

Fundamentals of Operations Research introduces systematic, quantitative methods for analyzing and optimizing complex decision-making problems in engineering, management, and applied sciences. The course focuses on building mathematical models that represent real-world systems and using analytical and computational techniques to obtain optimal or near-optimal solutions under given constraints. Key emphasis is placed on logical problem formulation, objective function development, and interpretation of results for practical decision support.

Learners are introduced to core concepts such as linear programming, transportation and assignment models, network optimization, inventory control, queuing theory, and basic decision analysis. Through illustrative examples and problem-solving exercises, the course demonstrates how Operations Research tools improve efficiency, reduce costs, and enhance resource utilization in industrial, service, and organizational settings. This foundation equips participants with the analytical mindset and quantitative skills required for advanced optimization and data-driven decision-making.

source: NPTEL[nptelhrd]

Course suitable for

Mechanics & Turbomachinery
Mechanical
Production

Key topics covered

introduction to linear programming formulations
simplex algorithm-minimization problems
simplex algorithm terminatiion
introduction to duality
transportation problems
assignment problem- Hungarian algorithm

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