Unit 1: Summary – Operations Research

Computer-Based Systems in Operations Research

1. Data, Information, and Information Systems

What is Data?

Data refers to raw, unorganized facts that need to be processed. Data can be numbers, characters, images, or other outputs from devices that collect input.

Examples:

A list of employee names and IDs

Sensor readings from a machine

Data in itself has no meaning until it is processed or organized.

What is Information?

Information is data that has been processed, organized, or structured in a meaningful way.

Example:

An employee performance report compiled from monthly data

A dashboard showing real-time sales statistics

Information is actionable—it supports decision-making and strategic planning.

Relationship between Data and Information

Data → Processing → Information → Decision Support

In a Computer-Based System (CBS), data is collected from various sources, processed through software or algorithms, and converted into information useful to decision-makers.

2. Computer-Based Information Systems (CBIS)

Definition

A Computer-Based Information System is a collection of hardware, software, data, people, and processes that work together to provide meaningful information to support decision-making in organizations.

Components of CBIS:

1.      Hardware – physical devices (servers, workstations)

2.    Software – programs that process data (databases, analytics tools)

3.    Data – raw facts

4.    People – IT professionals, end users

5.    Processes – policies and procedures used to collect, store, and analyze data

Example: Inventory Management System

·         Hardware: barcode scanners, servers

·         Software: inventory management software

·         Data: product IDs, stock levels

·         People: store staff, IT administrators

·         Processes: restocking rules, reorder alerts

3. Model of a Computer-Based Information System

A CBIS model consists of five core functions:

1.      Input – Captures raw data (e.g., customer orders)

2.    Processing – Converts data into meaningful formats

3.    Storage – Holds data for later use (e.g., databases)

4.    Output – Generates reports, dashboards

5.    Feedback – Helps improve system processes over time

Example Flow:

A sales transaction at a retail store → System logs the sale (Input) → Updates inventory levels (Processing) → Saves new stock count (Storage) → Notifies procurement (Output) → Management revises stock rules (Feedback)

 4. Introduction to Management Information System (MIS)

What is MIS?

A Management Information System (MIS) is a specialized CBIS that helps managers in strategic, tactical, and operational decision-making.

MIS supports:

·         Routine decisions like inventory reordering

·         Strategic planning using data trends

·         Monitoring performance using dashboards

Features of MIS:

·         Timely and accurate reports

·         User-friendly interface

·         Decision support tools

·         Integration with other systems (e.g., ERP)

Benefits of MIS:

·         Improves efficiency and productivity

·         Supports real-time decision-making

·         Reduces manual effort

·         Enhances communication and coordination

 Real-world Example:

In a hospital:

·         MIS tracks patient records, staff schedules, and medication stocks

·         Helps doctors retrieve patient histories instantly

·         Helps management decide on resource allocation

5. Decision Support Systems (DSS)

What is a DSS?

A Decision Support System is an interactive software-based system designed to help managers make decisions based on data analysis, models, and simulations.

Key Characteristics:

Supports non-routine, complex decisions

Allows “what-if” analysis

Combines human intuition with machine precision

Flexible and user-driven

Components of a DSS:

1.      Database Management System – Stores relevant data

2.    Model Base – Contains analytical tools (e.g., forecasting models)

3.    User Interface – Allows users to interact with system

DSS in Operations Research:

Optimization problems: choosing the best schedule, allocation, route

Simulation: testing a new production strategy

Resource Planning: managing multiple projects

Example:

A transportation company using DSS to find the most fuel-efficient delivery routes considering traffic, fuel cost, and vehicle capacity.

6. Knowledge-Based Systems (KBS)

What is a KBS?

A Knowledge-Based System is a computer program that uses artificial intelligence to emulate human reasoning. It stores knowledge in the form of rules and facts and makes inferences based on input.

Components:

Knowledge Base: Contains domain-specific facts and rules

Inference Engine: Uses logic to derive conclusions

User Interface: Allows users to interact with the system

Example:

Medical Expert System:

Symptoms are entered

The system applies medical rules to diagnose diseases and recommend treatments

Relevance to Operations Research:

Automates complex decision-making processes

Enhances human expertise with computational reasoning

Useful in resource scheduling, machine fault diagnosis, project risk analysis

Integration with Operations Research

Case: Manufacturing Optimization

A factory wants to:

·         Maximize output

·         Minimize waste

·         Ensure timely delivery

 How Systems Help:

Resource Management Areas

Key Takeaways

1.      Computer-Based Systems (CBS) are essential for modern operations research and decision-making.

2.    The transition from data → information → decision is at the heart of CBS and MIS.

3.    MIS provides managers with the tools to monitor, plan, and optimize.

4.    DSS supports critical decisions through models and simulations.

5.    KBS mimics expert knowledge, automating complex reasoning.

6.    These systems, when integrated, help manage capital, materials, and manpower more efficiently.

Real-Life Use Cases

Conclusion

Computer-Based Systems form the nervous system of modern organizations, guiding them through data-driven decisions, smart optimization, and strategic planning.

As the business world becomes more data-driven, familiarity with systems like MIS, DSS, and KBS is not just an asset—it’s a requirement for leading impactful solutions in operations and engineering challenges.