Networks and Logistics in Shipping

optimized liner-operating transshipment formulation for real world applications


Dossier / Travail de Séminaire, 2014

24 Pages, Note: 1,3


Extrait


Table of Contents

List of Abbreviations

List of Figures

List of Tables

List of Appendices

1.Introduction

2.Transshipment Problem
2.1 Network A Characteristics
2.2 Network A Specifications
2.3 Model1
2.3.1 Task
2.3.2 Optimum Flow
2.4 Model 2
2.4.1 Task
2.4.2 Optimum Flow
2.5 Model 3
2.5.1 Task
2.5.2 Optimum Flow
2.6 Evaluation

3.RealWorldApplication.
3.1 Problemssolved
3.2 Problemsnotaddressed

4.ImpactofConstraints
4.1 CapacityConstraints
4.2 EnvironmentalConstraints

5.ComplexModel
5.1 Task
5.2 OptimumFlow

6.Conclusion

Sources

List of Abbreviations

illustration not visible in this excerpt

List of Figures

Figure (1): Schematic representation of the network

Figure (2): Model 1

Figure (3): Model 2

Figure (4): Model 3

Figure (5): Existing and possible future ECAs

List of Tables

Table (1): Supply and demand of the network

Table (2): Capacity issues at port 4

Table (3): Additional Constraints

List of Appendices

Appendix

(1): A Home Assignment Appendix

(2): B Home Assignment Appendix

(3): C Home Assignment

1. Introduction

Network- and Logistic-Operators increasingly use computerized methods to optimize logistical processes. Since transport is a field of application, the use of methodologies is particularly relevant to find valuable solutions for real world issues (Rodrigue, Comtois und Slack, The Geography of Transport Systems 2006, VIII). This paper uses the example of a fictitious liner-shipping operator to analyze the value of an optimized transshipment formulation in relation to the actual application.

Currently the shipping industry is facing several enormous challenges at the same time. The impact of global economic downturn, the crisis in the main shipping sectors and the changes in the pattern of world trade all profoundly affect the maritime transport industry (De Monie, Rodrigue und Notteboom 2011). Additionally the fluctuating fuel-prices and notably the implementation of barriers by regulatory bodies such as the declaration of Emission Controlled Areas (ECA) are pressurizing the maritime transport sector. Since freight rates are currently rather low, transport operators focus on minimizing their operation expenditures (OPEX) by optimizing the allocation of their resources. Especially liner-operators use these computerized methods to save costs, even though the introduction of containers themselves enabled an increased flexibility of freight transport and reduced transshipment costs and delays in general already (Rodrigue, Comtois und Slack, The Geography of Transport Systems 2006, 24). To what extend the use of these methods serves real world applications will be analyzed by discussing the problems solved by this method and identifying further issues that are missed out. The focus lies on issues that have an impact on the optimum flow or the final costs. After these issues have been taken into account, this paper concludes with a short summery of the results.

2. Transshipment Problem

2.1 Network-Characteristics

A fictitious liner-shipping operator is facing the following network: The network consists of two ports in region I, namely port 1 and 2, two transshipment hubs, namely port 3 and 4, and three ports in region II, namely ports 5, 6 and 7.

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Figure (1): Schematic representation of the network.

2.2 Network-Specifications

The given network-specifications are shown in Table (1) and Table (2). Region I represents the suppliers with a given amount of supply while region II represents the consumers with a given amount of demand. The transshipment hubs face several capacity issues. These specifications lead to constraints in the overall- flow of the network.

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Table (1): Supply and demand of the network.

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Table (2): Capacity issues at port 4.

The capacity constraints are measured in TEU sizes. As a consequence one FEU unit was counted double in this context. For example the constraint for all units from port 1 forwarded to port 4, to be less or equal to 65.000, is translated into the formula:

illustration not visible in this excerpt

The costs for moving one TEU or FEU from one point to another are shown in Figure (1) “Schematic representation of the network”. The left number in the brackets stands for the costs of moving one TEU; the right number stands for the costs of moving one FEU for the specific connection.

2.3 Model 1

2.3.1 Task

“ For the given network find the optimum flow of shipments and the total cost. ”

2.3.2 Optimum Flow

In order to find the optimum flow for the given network, the characteristics and specifications have been translated into parameters and put into a system of linear equations. This system was integrated in the software MS Excel and used the function “Solver” to find an optimal solution.

Appendix A offers this system and the calculated solution.

The following solution was found in Figure (2):

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Figure (2): Model 1

This model achieves the lowest total cost when all TEU and FEU units from port 1 only use port 3 as a transshipment hub. There are no shipments from port 1 to port 4. The optimum solution for port 2 is to split the TEU units between port 3 and 4. Port 4 is not attractive for FEU shipments in this model due to its competition with port 3. The optimum flow minimizes the total cost to 22.760.000$.

2.4 Model 2

2.4.1 Task

“ Consider the following flow constraints and estimate the optimum flow of shipments and the total cost. ”

illustration not visible in this excerpt

Table (3): Additional Constraints.

2.4.2 Optimum Flow

Appendix B offers this system and solution.

The following solution was found in Figure (3):

illustration not visible in this excerpt

Figure (3): Model 2

In this model the additional constraints, shown in Table (3), have affected the flow in the network and the total cost. The TEU flow from port 1 to 3 decreased while the TEU flow from port 1 to 4 got introduced. From this follows a decreasing TEU flow from port 3 to port 6 and an increasing TEU flow from port 4 to 6.

Since the new FEU-constraints offer even larger capacities now, even though they have not been reached before, there are no changes in the FEU flow.

The new TEU flow creates additional costs about 220.000$ and results in the new total cost of 22.980.000$. This is an increase of 0,97 percent in comparison to the total cost in model 1.

2.5 Model 3

2.5.1 Task

“ Consider that the seas off Port 6 are declared as ECA and 20 increase of the cost is expected. Find the optimum flow of shipments and the total cost. ”

[...]

Fin de l'extrait de 24 pages

Résumé des informations

Titre
Networks and Logistics in Shipping
Sous-titre
optimized liner-operating transshipment formulation for real world applications
Université
Hamburg School of Business Administration gGmbH  (Maritime School)
Cours
Shipping: Networks and Logistics
Note
1,3
Auteur
Année
2014
Pages
24
N° de catalogue
V284799
ISBN (ebook)
9783656869559
ISBN (Livre)
9783656869566
Taille d'un fichier
1830 KB
Langue
anglais
Mots clés
Networks, Logistics, Shipping, optimize, liner-operating, transshipment, optimum flow, stockfisch, hans-christian
Citation du texte
Diplom Kaufmann Hans-Christian Stockfisch (Auteur), 2014, Networks and Logistics in Shipping, Munich, GRIN Verlag, https://www.grin.com/document/284799

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