Simulation is one of the most important methods utilizing models to study system.Simulation technology has developed for nearly 50 years. It has been applied widelyand effectively in aerospace， military， automation， electric power and other fields. Withthe development of computer technology and in-depth research in all areas， systemsimulation technology is becoming more and more mature and its application fields areexpanding.
　　Recently， more and more people are paying attention to modern logistics. It hasmany features， including wide coverage， comprehensiveness and broad involvement. Itcovers industry， agriculture and service industry， and it integrates a number of areas inmanagement and engineering. It involves many processes such as transportation，warehousing， packaging， service， information， and so on. Logistics is not only related to the enterprises' development， but also plays a vital role in the development of the national economy. Therefore， people pursue the common goal of promoting the transformation from traditional logistics to modern logistics. The research on introducing system simulation technology into modern logistics can assist people to scientifically plan and design logistics systems， control logistics operation process， and allocate logistics resources. It can promote the overall optimization of logistics system. At the same time， the vigorous development of the logistics industry will also promote the development of system simulation technology and open up a new field for the application of system simulation.

　　Simulation is one of the most important methods utilizing models to study system.Simulation technology has developed for nearly 50 years. It has been applied widelyand effectively in aerospace， military， automation， electric power and other fields. Withthe development of computer technology and in-depth research in all areas， systemsimulation technology is becoming more and more mature and its application fields areexpanding.
　　Recently， more and more people are paying attention to modern logistics. It hasmany features， including wide coverage， comprehensiveness and broad involvement. Itcovers industry， agriculture and service industry， and it integrates a number of areas inmanagement and engineering. It involves many processes such as transportation，warehousing， packaging， service， information， and so on. Logistics is not only related to the enterprises' development， but also plays a vital role in the development of the national economy. Therefore， people pursue the common goal of promoting the transformation from traditional logistics to modern logistics. The research on introducing system simulation technology into modern logistics can assist people to scientifically plan and design logistics systems， control logistics operation process， and allocate logistics resources. It can promote the overall optimization of logistics system. At the same time， the vigorous development of the logistics industry will also promote the development of system simulation technology and open up a new field for the application of system simulation.
　　In order to facilitate teaching and make things convenient for readers to self-study，we combine the basic principles of system simulation and instructions of software operation together. The basic principles are introduced in the first six chapters. Among them， Chapter 1 is an overview， which focuses on history， features， applications and related technologies of system simulation. Chapter 2 introduces the basic knowledge of system simulation， including basic concepts， discrete event system simulation， single server queuing system simulation and single item inventory system simulation. Chapter 3 introduces the basic concepts of random numbers and random variables，commonly-used distribution， random number generator， random number performance testing， and the methods of generating random variables. Chapter 4 introduces the simulation input data Modeling. Chapter 5 introduces several major system simulation algorithms， including event scheduling， activity scanning， three-stage scanning， and process interaction. Chapter 6 presents concepts and methods of simulation output data analysis and evaluation. AnyLogic software is introduced in Chapter 7 to Chapter 10.Among them， Chapter 7 gives a brief introduction of AnyLogic simulation software.Chapter 8 illustrates an guidance ofAgent-based modeling in AnyLogic. Chapter 9 is an advanced tutorial of discrete-event system simulation and the system dynamic simulation is illustrated in chapter 10.
　　The application of AnyLogic software starts from the easy to the difficult and complicated. Many of the basic concepts of AnyLogic will be first introduced and defined in the previous chapters， and then the following chapters will elaborate them and give a guidance. Readers can use this tutorial to learn repetitively.
　　We gratefully acknowledge the cheerful aid of Southwest Jiaotong University and AnyLogic team of China. Many undergraduates in our research team devote themselves into the edition work of this book including Yijing Chen， Miao Lai， Hengqing Che， Mao Lao， Wei Zhang， Shasha Liu， Junwen Yang， etc. Especially Yue Hu， Wen Cui， Peng Cui，Juan Li revised Chapter 7， 8， 9， 10 respectively， and thanks to them all， including the editors and other kind people.

Chapter 1 Outline
1．1 Systems and System Model
1．2 System Simulation Outline
1．3 The Characteristics of System Simulation
1．4 Logistics System Simulation and Technology
1．5 Trend of System Simulation

Chapter 2 Basic Knowledge of System Simulation
2．1 The Continuous System and Discrete System
2．2 Discrete Event System Simulation Method
2．3 Queuing System
2．4 Inventory System
2．5 Single-channel Queuing System Simulation
2．6 Single-item Inventory System Simulation

Chapter 3 Random-Number and Random-Variable
3．1 Deterministic System and Random System
3．2 Random-number and Random-variable
3．3 Random-number Generation
3．4 Tests for Random Numbers
3．5 Random-variable Generation

Chapter 4 Processing of Input Modeling
4．1 Overview of Input Modeling
4．2 Data Collection and Data Processing
4．3 Assumptions of Data Distribution
4．4 Parameter Estimation
4．5 Goodness-of-Fit Test

Chapter 5 Methodologies of Discrete Event Simulation
5．1 Event Scheduling
5．2 Activity Scanning
5．3 Process Interaction

Chapter 6 Output Analysis of System Simulation
6．1 Introduction
6．2 Types of System Simulation
6．3 Interval Estimation and Confidence Intervals
6．4 Output Analysis of Termination-type Simulation
6．5 Output Analysis of Steady-state Simulation
6．6 Comparison of Random Varibles
6．7 Sensitivity Analysis
6．8 Orthogonal Design
6．9 Parameter Optimization

Chapter 7 Introduction and Installing of Anylogic
7．1 Introduction of Anylogic
7．2 Installing of Anylogic

Chapter 8 Agent Based Modeling with Anylogic
8．1 Market Model
8．2 Creating the Agent Population
8．3 Defining a Consumer Behavior
8．4 Adding A Chart to Visualize the Model Output
8．5 Adding Word of Mouth Effect
8．6 Considering Product Discards
8．7 Considering Delivery Time
8．8 Simulating Consumer Impatience
8．9 Comparing Model Runs with Different Parameter Values

Chapter 9 Discrete-event Modeling with AnyLogic
9．1 Job Shop Model
9．2 Creating A Simple Model
9．3 Adding Resources
9．4 Creating 3D Animation
9．5 Modeling Pallet Delivery by Trucks
9．6 Modeling CNC Machines

Chapter 10 System Dynamics Modeling with AnyLogic
10．1 Creating a Stock and Flow Diagram
10．2 Adding A Plot to Visualize Dynamics
10．3 Parameter Variation Experiment

Main Reference