Cargando…
Optimization of Logistics.
This book aims to help engineers, Masters students and young researchers to understand and gain a general knowledge of logistic systems optimization problems and techniques, such as system design, layout, stock management, quality management, lot-sizing or scheduling. It summarizes the evaluation an...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Wiley,
2012.
|
| Colección: | ISTE.
|
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Cover; Dedication; Title; Copyright; Chapter 1. Modeling and Performance Evaluation; 1.1. Introduction; 1.2. Markovian processes; 1.2.1. Overview of stochastic processes; 1.2.2. Markov processes; 1.2.3. Markov chains; 1.3. Petri nets; 1.3.1. Introduction to Petri nets; 1.3.2. Non-autonomous Petri nets; 1.3.3. Timed Petri nets; 1.3.4. Continuous Petri nets; 1.3.5. Colored Petri nets; 1.3.6. Stochastic Petri nets; 1.4. Discrete-event simulation; 1.4.1. The role of simulation in logistics systems analysis; 1.4.2. Components and dynamic evolution of systems.
- 1.4.3. Representing chance and the Monte Carlo method1.4.4. Simulating probability distributions; 1.4.5. Discrete-event systems; 1.5. Decomposition method; 1.5.1. Presentation; 1.5.2. Details of the method; Chapter 2. Optimization; 2.1. Introduction; 2.2. Polynomial problems and NP-hard problems; 2.2.1. The complexity of an algorithm; 2.2.2. Example of calculating the complexity of an algorithm; 2.2.3. Some definitions; 2.2.4. Complexity of a problem; 2.3. Exact methods; 2.3.1. Mathematical programming; 2.3.2. Dynamic programming; 2.3.3. Branch and bound algorithm; 2.4. Approximate methods.
- 2.4.1. Genetic algorithms2.4.2. Ant colonies; 2.4.3. Tabu search; 2.4.4. Particle swarm algorithm; 2.5. Multi-objective optimization; 2.5.1. Definition; 2.5.2. Resolution methods; 2.5.3. Comparison criteria; 2.5.4. Multi-objective optimization methods; 2.6. Simulation-based optimization; 2.6.1. Dedicated tools; 2.6.2. Specific methods; Chapter 3. Design and Layout; 3.1. Introduction; 3.2. The different types of production system; 3.3. Equipment selection; 3.3.1. General overview; 3.3.2. Equipment selection with considerations of reliability; 3.4. Line balancing.
- 3.4.1. The classification of line balancing problems3.4.2. Solution methods; 3.4.3. Literature review; 3.4.4. Example; 3.5. The problem of buffer sizing; 3.5.1. General overview; 3.5.2. Example of a multi-objective buffer sizing problem; 3.5.3. Example of the use of genetic algorithms; 3.5.4. Example of the use of ant colony algorithms; 3.5.5. Example of the use of simulation-based optimization; 3.6. Layout; 3.6.1. Types of facility layout; 3.6.2. Approach for treating a layout problem; 3.6.3. The best-known methods; 3.6.4. Example of arranging a maintenance facility.
- 3.6.5. Example of laying out an automotive workshopChapter 4. Tactical Optimization; 4.1. Introduction; 4.2. Demand forecasting; 4.2.1. Introduction; 4.2.2. Categories and methods; 4.2.3. Time series; 4.2.4. Models and series analysis; 4.3. Stock management; 4.3.1. The different types of stocked products; 4.3.2. The different types of stocks; 4.3.3. Storage costs; 4.3.4. Stock management; 4.3.5. ABC classification method; 4.3.6. Economic quantities; 4.3.7. Replenishment methods; 4.4. Cutting and packing problems; 4.4.1. Classifying cutting and packing problems.