Liner Ship Fleet Planning Models and Algorithms 1st Edition by Tingsong Wang, Shuaian Wang, Qiang Meng 0128115033 9780128115039

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Product details:

ISBN-10 :  0128115033 

ISBN-13 :  9780128115039

Author : Tingsong Wang, Shuaian Wang, Qiang Meng 

Liner Ship Fleet Planning: Models and Algorithms systematically introduces the latest research on modeling and optimization for liner ship fleet planning with demand uncertainty. Container shipping companies have struggled since the financial crisis of 2007-2008, making it critical for them to make informed decisions about their fleet planning and development.

Current and future shipping professionals require systematic approaches for investigating and solving their fleet planning problems, as well as methodologies for addressing their other shipping responsibilities. Liner Ship Fleet Planning addresses these needs, providing the most recent quantitative research of liner shipping in maritime transportation. The research and methods provided assist those tasked with optimizing shipping efficiency and fleet deployment in the face of uncertain demand. Suitable for those with any level of quantitative background, the book serves as a valuable resource for both maritime academics, and shipping professionals involved in planning and scheduling departments.

 

Liner Ship Fleet Planning. Models and Algorithms 1st Table of contents:

Part One: Introduction
Chapter One: Introduction to Shipping Services
Abstract
Seaborne Trade
Container Ports
Maritime Transportation
Chapter Two: Liner Ship Fleet Planning
Abstract
Introduction
Fleet Size and Mix
Fleet Deployment
Fleet Planning
Research Limitations and Gaps
Summary
Part Two: Mathematical Modeling
Chapter Three: Introduction to Stochastic Programming
Abstract
Motivation
Examples
Summary
Chapter Four: Chance-Constrained Programming
Abstract
Introduction
Selected Applications
Summary
Chapter Five: Two-Stage Stochastic Model
Abstract
Introduction
Selected Applications
Summary
Part Three: Solution Algorithms
Chapter Six: Sample Average Approximation
Abstract
Introduction
Theoretical Background
Convergence
Lower bound
Feasible Solutions
Examples
Summary
Chapter Seven: Dual Decomposition and Lagrangian Relaxation
Abstract
Introduction
Lagrangian Relaxation
Dual Decomposition
Summary
Part Four: Case Studies
Chapter Eight: Liner Ship Fleet Planning Problem With an Individual Chance-Constrained Service Level
Abstract
Introduction
Problem Description, Assumptions, and Notations
Model Development
Numerical Example
Summary
Chapter Nine: Liner Ship Fleet Planning Problem With a Joint Chance-Constrained Service Level
Abstract
Introduction
Model Development
Solution Algorithm
Numerical Example
Summary
Chapter Ten: Liner Ship Fleet Planning with Expected Profit Maximization
Abstract
Introduction
Model Development
Solution Algorithm
Numerical Example
Summary
Chapter Eleven: Multiperiod Liner Ship Fleet Planning
Abstract
Introduction
Problem Statement
Model Development
Solution Algorithm
Computational Results
Summary
Part Five: Conclusion
Chapter Twelve: Conclusions and Future Outlook

 

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