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1.2.6- Operations Research (OR)

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By Dr.M.MuthuKrishnan

 


Definition

Operations Research (OR) is a scientific and quantitative approach to decision-making that uses mathematical models, statistics, and optimization techniques to find the best possible solution to complex industrial and managerial problems.

Objectives of Operations Research

  • To achieve optimal utilization of resources

  • To minimize cost or maximize profit/output

  • To improve decision-making

  • To handle complex problems involving uncertainty and constraints

Features of Operations Research

  • Uses mathematical and analytical models

  • System-oriented approach

  • Interdisciplinary in nature

  • Focuses on optimization

  • Data-based and scientific

Basic Steps in OR

  1. Problem formulation

  2. Construction of a mathematical model

  3. Collection of relevant data

  4. Solution of the model

  5. Testing and validation

  6. Implementation of results

Common OR Techniques

  • Linear Programming (LP)

  • Transportation and Assignment Models

  • Inventory Models

  • Queuing Theory

  • Network Models (PERT/CPM)

  • Simulation

  • Game Theory

  • Decision Theory

Applications of Operations Research

  • Production planning and scheduling

  • Inventory control

  • Transportation and logistics

  • Machine utilization

  • Project management

  • Marketing and finance decisions

Example (Industrial)

A factory wants to decide the optimal production mix of two products using limited labor and machine hours. OR techniques like Linear Programming help determine the best combination to maximize profit.

Importance of OR

  • Improves efficiency

  • Reduces operational cost

  • Enhances productivity

  • Supports scientific management

Examples of OR

1. Manufacturing

  • Problem: How many units of each product to produce to maximize profit, given limited resources.

  • OR Technique: Linear Programming (LP)

  • Example: A factory produces chairs and tables. Each requires different amounts of wood and labor. OR helps determine the optimal number of chairs and tables to produce to maximize profit.

2. Transportation & Logistics

  • Problem: Minimize shipping costs while meeting demand at multiple locations.

  • OR Technique: Transportation Problem / Linear Programming

  • Example: A company has warehouses in 3 cities and customers in 5 cities. OR helps find the cheapest way to transport products from warehouses to customers.

3. Inventory Management

  • Problem: How much stock to keep to minimize cost without running out.

  • OR Technique: Inventory Models (EOQ – Economic Order Quantity)

  • Example: A store wants to determine the optimal order quantity of a product to reduce holding costs and stockouts.

4. Project Scheduling

  • Problem: Completing a project in minimum time using limited resources.

  • OR Technique: PERT/CPM (Project Evaluation and Review Technique / Critical Path Method)

  • Example: Construction of a building where OR helps schedule tasks to complete the project fastest.

5. Queuing & Service Systems

  • Problem: Reducing waiting times in a service system like banks or hospitals.

  • OR Technique: Queuing Theory

  • Example: A hospital wants to know how many doctors are needed to minimize patient waiting time.

6. Network Optimization

  • Problem: Finding the shortest route or minimum cost path.

  • OR Technique: Graph Theory / Network Models

  • Example: Finding the shortest delivery route for a courier company to save fuel and time.

7. Decision Making Under Uncertainty

  • Problem: Choosing the best investment considering risks.

  • OR Technique: Decision Analysis / Simulation

  • Example: A company deciding between multiple projects with uncertain future returns uses OR techniques to select the best option.

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