System Reliability Analysis for a Stochastic Liner Container Shipping Service with Stochastic Terminals

Author:

Nguyen Thi-Phuong1,Liao Ya-Ting2,Lin Yi-Kuei2345,Chang Ping-Chen6ORCID

Affiliation:

1. College of Management, National Chin-Yi University of Technology, Taichung 411, Taiwan

2. Department of Industrial Engineering and Management, National Yang Ming Chiao Tung University, Hsinchu 300, Taiwan

3. Department of Business Administration, Asia University, Taichung 413, Taiwan

4. Department of Business Administration, Chaoyang University of Technology, Taichung 413, Taiwan

5. Department of Mathematics; Computer Science & Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India

6. Department of Industrial Engineering and Management, National Quemoy University, Kinmen 892, Taiwan

Abstract

In the container shipping industry, a company could have an advantage over its competitors while its liner container shipping system (LCSS) can successfully transport the requested demand. However, some uncertainties such as unstable sea state, terrible weather, sailor’s negligence, and the condition of vessels would affect the number of slots on the vessel to place containers when shipping on different legs. Thus, that number should be regarded as stochastic. At the container terminal, containers are loaded from and unloaded to the vessel ship by the quay cranes. The number of available quay cranes at each terminal is also stochastic because of the reservation of other competitors. Therefore, this study proposes an algorithm that constructs an LCSS as a stochastic liner container shipping network (SLCSN) model to analyze the network reliability. Network reliability is defined as the probability that all vessels in the SLCSN can satisfy the demands within the time threshold. For an executive of the liner container shipping company, the network reliability can be utilized as the performance indicator to make an appropriate managerial decision.

Publisher

World Scientific Pub Co Pte Ltd

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Energy Engineering and Power Technology,Aerospace Engineering,Safety, Risk, Reliability and Quality,Nuclear Energy and Engineering,General Computer Science

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