Simulation and modeling - Syllabus

Overview of E-commerce and its significance in the digital age.

Understanding the differences between E-business and E-commerce.

Key characteristics and benefits of E-commerce.

Types of E-commerce models and their applications.

Evolution and development of E-commerce over time.

Understanding the components of E-commerce framework including People, Public Policy, Marketing and Advertisement, Support Services, and Business Partnerships.

Overview of different types of E-commerce including B2C, B2B, C2B, C2C, M-Commerce, U-commerce, Social-Ecommerce, and Local E-commerce.

Common obstacles and difficulties faced in E-commerce.

Current state and trends of E-commerce in Nepal.

A queuing system is a mathematical model that describes the behavior of customers arriving at a service facility, waiting in a queue, and being served by one or more servers. It is used to analyze and optimize the performance of various systems, such as call centers, hospitals, and manufacturing systems.

Markov chains are a mathematical system that undergoes transitions from one state to another, where the probability of transitioning from one state to another is dependent on the current state and time elapsed. They are used to model complex systems, such as communication networks, population dynamics, and financial markets.

Differential partial equations are a type of mathematical equation that involves an unknown function and its partial derivatives with respect to one or more independent variables. They are used to model various physical systems, such as heat diffusion, wave propagation, and fluid dynamics.

Introduction to vector spaces and subspaces, including their definitions and properties.

Exploration of null spaces, column spaces, and linear transformations, including their relationships and applications.

Discussion of linearly independent sets and bases, including their definitions, properties, and importance in vector spaces.

Introduction to coordinate systems, including their definition, importance, and applications in vector spaces.

Introduction to system requirements, including traditional and contemporary methods for determining system requirements, requirements management tools, and requirements determination using agile methodologies.

Introduction to system process requirements, including process modeling, data flow diagramming, and modeling logic with decision tables.

Introduction to system data requirements, including conceptual data modeling, E-R modeling, and business rules, as well as the role of packaged conceptual data models and database patterns.

Methods for identifying and eliminating internal bias in simulation models to improve accuracy and reliability.

Overview of software tools used for simulation, including their features and applications.

Introduction to programming languages specifically designed for simulation, such as GPSS.

In-depth study of the GPSS simulation language, including its syntax, features, and examples.

Analysis of real-world examples of simulation in different domains, highlighting their objectives, methodologies, and outcomes.

Concepts and techniques for designing and developing simulation models, including model types and their applications.

Methods for building mathematical models that can be used for simulation, including equation-based and algorithmic models.

A method for selecting the essential prime implicants in a Boolean function. It is used to minimize Boolean expressions and implement digital circuits.