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Green Maritime Transportation: Speed and Route Optimization

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Abstract

Among the spectrum of logistics-based measures for green maritime transportation, this chapter focuses on speed optimization. This involves the selection of an appropriate speed by the vessel, so as to optimize a certain objective. As ship speed is not fixed, depressed shipping markets and/or high fuel prices induce slow steaming which is being practised in many sectors of the shipping industry. In recent years the environmental dimension of slow steaming has also become important, as ship emissions are directly proportional to fuel burned. Win-win solutions are sought, but they will not necessarily be possible. The chapter presents some basics, discusses the main trade-offs and also examines combined speed and route optimization problems. Some examples are finally presented so as to highlight the main issues that are at play.

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Notes

  1. 1.

    The 18,000 TEU yardstick as the world’s largest containership size was fated to be surpassed. As this chapter was being completed, the baton was being held by the 19,224 TEU MSC Oscar, of the Mediterranean Shipping Company (MSC).

  2. 2.

    This is 24 times the ship speed in knots. We use this unit to avoid carrying the number 24 through the calculations. One knot is one nautical mile per hour (1.852 km per hour) and is the typical unit of ship speed.

  3. 3.

    WS is a nondimensional index measuring the spot rate and is exclusively used in the tanker market. For a specific route, WS is proportional to the spot rate on that route (in $/tonne) and is normalized by the ‘base rate’ on that route. See Stopford (2009) for a detailed definition.

  4. 4.

    The assumption that F is independent of charter duration is valid if the charter duration is within a reasonably narrow range. For large variations of time charter duration (e.g. a few months versus a multi-year charter), we expect that F will generally vary with charter duration.

  5. 5.

    In terms of ship size, this corresponds roughly to a feeder containership of about 1,000 TEU capacity. It could also be a product carrier or a small bulk carrier.

  6. 6.

    As this book was being finalized, an unprecedented decrease in oil prices was taking place. However, as charter rates fell too, a definitive statement on the effect of this development on average ship or fleet speeds was not possible.

Abbreviations

AIS:

Automatic Identification System

CEO:

Chief Executive Officer

CIF:

Cost Insurance Freight

CO2 :

Carbon dioxide

COA:

Contract Of Affreightment

DWT:

Deadweight Ton

GHG:

Green House Gas

GPCI:

Global Ports Congestion Index

HFO:

Heavy Fuel Oil

IMO:

International Maritime Organization

LNG:

Liquefied Natural Gas

LPG:

Liquefied Petroleum Gas

MBM:

Market Based Measure

MCR:

Maximum Continuous Rating

MEPC:

Marine Environment Protection Committee

MSC:

Mediterranean Shipping Company

NTUA:

National Technical University of Athens

OPEX:

Operating Expenses

OR/MS:

Operations Research/Management Science

Ro/Pax:

Ro/Ro Passenger

Ro/Ro:

Roll On Roll Off

SECA:

Sulphur Emissions Control Area

SOx :

Sulphur oxides

TEU:

Twenty ft Equivalent Unit

VLCC:

Very Large Crude Carrier

WS:

World Scale (index)

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Acknowledgments

Work on this chapter has been supported in part by various sources, including the Lloyd’s Register Foundation (LRF) in the context of the Centre of Excellence in Ship Total Energy-Emissions-Economy at the National Technical University of Athens (NTUA), the authors’ former affiliation. LRF helps to protect life and property by supporting engineering-related education, public engagement and the application of research. This work has also been supported in part by an internal grant at the Technical University of Denmark (DTU).

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Correspondence to Harilaos N. Psaraftis .

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Appendix: Taxonomy of Speed Papers, Amended from Psaraftis and Kontovas (2013)

Appendix: Taxonomy of Speed Papers, Amended from Psaraftis and Kontovas (2013)

Table has 7 parts, of 7 entries each. Two entries have two references each. Total references: 51

Taxonomy part I

Taxonomy parameter\ paper

Alderton (1981)

Alvarez (2009)

Andersson, Fagerholt, and Hobbesland (2014)

Bausch, Brown, and Ronen (1998)

Benford (1981)

Brown, Graves, and Ronen (1987)

Cariou (2011)

Optimization criterion

Profit

Cost

Cost

Cost

Cost

Cost

Cost

Shipping market

General

Liner

Ro/Ro

Tanker/barge

Coal

Tanker

Container

Decision maker

Owner

Owner

Owner

Owner

Owner

Owner

Owner

Fuel price an explicit input

Yes

Yes

No

Yes

No

No

Yes

Freight rate an input

Input

No

Implicit

No

No

No

No

Fuel consumption function

Cubic

Cubic

General

Unspecified

Cubic

Unspecified

Cubic

Optimal speeds in various legs

Yes

Yes

Yes

No

No

Only ballast

No

Optimal speeds as function of payload

Yes

Yes

Yes

No

No

No

No

Logistical context

Fixed route

Joint routing and fleet deployment

Fleet deployment

Routing and scheduling

Fleet deployment

Routing and scheduling

Fixed route

Size of fleet

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Add more ships an option

Yes

No

Yes

No

No

No

Yes

Inventory costs included

Yes

No

No

No

No

No

No

Emissions considered

No

No

No

No

No

No

Yes

Modal split considered

No

No

No

No

No

No

No

Ports included

Yes

Yes

No

Yes

No

No

No

Taxonomy part II

Taxonomy parameter\ paper

Cariou and Cheaitou (2012)

Chang and Wang (2014)

Corbett, Wang, and Winebrake (2010)

Devanney (2007)

Devanney (2010)

Doudnikoff and Lacoste (2014)

Du, Chen, Quan, Long, and Fung (2011)

Wang, Meng, and Liu (2013a, b)

Optimization criterion

Cost

Cost

Profit

Profit

Cost or profit

Cost

Fuel consumption

Shipping market

Container

General

Container

Tanker

Tanker (VLCC)

Liner

Container

Decision maker

Owner

Owner

Owner

Owner

Owner or charterer

Owner

Owner

Fuel price an explicit input

Yes

Yes

Yes

Yes

Yes

Yes

No

Freight rate an input

No

Yes

Input

Computed

Computed

No

No

Fuel consumption function

Cubic

Cubic

Cubic

Cubic

General

Cubic

Non-linear

Optimal speeds in various legs

No

No

No

Yes

Yes

Yes

Yes

Optimal speeds as function of payload

No

No

No

No

No

No

No

Logistical context

Fixed route

Fixed route

Fixed route

World oil network

Fixed route

Fixed route in SECAs

Berth allocation

Size of fleet

Multiple ships

One ship

Multiple ships

Multiple ships

One ship

Multiple ships

Multiple ships

Add more ships an option

Yes

No

Yes

Yes

Yes

No

No

Inventory costs included

Yes

No

No

Yes

Yes

No

No

Emissions considered

Yes

No

Yes

No

No

Yes

Yes

Modal split considered

No

No

No

No

No

No

No

Ports included

Yes

Yes

No

Yes

No

No

No

Taxonomy part III

Taxonomy parameter\ paper

Eefsen and Cerup-Simonsen (2010)

Faber, Freund, Köpke, and Nelissen (2010)

Fagerholt (2001)

Fagerholt, Laporte, and Norstad (2010)

Fagerholt, Gausel, Rakke, and Psaraftis (2015)

Fagerholt and Ronen (2013)

Gkonis and Psaraftis (2012)

Optimization criterion

Cost

N/A

Cost

Fuel consumption

Cost

Profit

Profit

Shipping market

Container

Various

General

Liner

Ro/Ro

Tramp

Tanker, LNG, LPG

Decision maker

Owner

N/A

Owner

Owner

Owner

Owner

Owner

Fuel price an explicit input

Yes

No

No

No

Yes

No

Yes

Freight rate an input

No

No

No

No

No

Implicit

Input

Fuel consumption function

Cubic

Cubic

Cubic

Cubic

Cubic

General

General

Optimal speeds in various legs

No

No

Yes

Yes

Yes

Yes

Yes

Optimal speeds as function of payload

No

No

No

No

No

No

No

Logistical context

Fixed route

Fixed route

Pickup and delivery

Fixed route

Route & speed selection in SECAs

Pickup and delivery

Fixed route

Size of fleet

Multiple ships

Multiple ships

Multiple ships

One ship

One ship

Multiple ships

Multiple ships

Add more ships an option

Yes

Yes

No

No

No

No

Yes

Inventory costs included

Yes

No

No

No

No

No

Yes

Emissions considered

Yes

Yes

No

Yes

Yes

No

Yes

Modal split considered

No

No

No

No

No

No

No

Ports included

Yes

No

No

No

No

No

Yes

Taxonomy part IV

Taxonomy parameter\ paper

Hvattum et al. (2013)

Kapetanis et al. (2014)

Kontovas and Psaraftis (2011)

Lang and Veenstra (2010)

Lindstad, Asbjørnslett, and Strømman (2011)

Lo and McCord (1998)

Magirou et al. (2015)

Optimization criterion

Fuel consumption

Profit

Cost

Fuel costs

Pareto analysis

Fuel consumption

Profit

Shipping market

General

Drybulk

Container

Container

All major ship types

General

General

Decision maker

Owner

Owner

Charterer

owner

Owner

Ship’s master

Owner

Fuel price an explicit input

No

Yes

Yes

No

Yes

No

Yes

Freight rate an input

No

Yes

Input

No

No

No

Yes

Fuel consumption function

Convex

General

Cubic

linearized

Cubic

Cubic

Cubic

Optimal speeds in various legs

Yes

Yes

Yes

No

No

N/A

Yes

Optimal speeds as function of payload

No

Yes

Yes

No

Yes

No

No

Logistical context

Fixed route

Fixed route

Fixed route

Vessel arrival planning

Fixed route

Weather routing

Fixed route

Size of fleet

One ship

Multiple ships

Multiple ships

Multiple ships

Multiple ships

One ship

One ship

Add more ships an option

No

Yes

Yes

No

Yes

No

No

Inventory costs included

No

Yes

Yes

No

Yes

No

No

Emissions considered

Yes

Yes

Yes

No

Yes

No

No

Modal split considered

No

No

No

No

No

No

No

Ports included

No

Yes

Yes

Yes

Yes

No

 

Taxonomy part V

Taxonomy parameter\ paper

Meng and Wang (2011)

Norlund and Gribkovskaia (2013)

Norstad et al. (2011)

Notteboom and Vernimmen (2010)

Perakis and Papadakis (1989)

Perakis (1985)

Perakis and Jaramillo (1991)

Optimization criterion

Cost

Cost

Cost

Cost

Cost

Cost

Cost

Shipping market

Liner

Offshore supply vessels

Tramp

Container

Tramp

Tramp

Liner

Decision maker

Owner

Owner

Owner

Owner

Owner

Owner

Owner

Fuel price an explicit input

Yes

No

No

Yes

Yes

No

Yes

Freight rate an input

No

No

No

No

No

No

Yes

Fuel consumption function

Cubic

Cubic

Cubic

Unspecified

General

Cubic

Cubic

Optimal speeds in various legs

No

Yes

Yes

No

Yes

No

Yes

Optimal speeds as function of payload

No

No

No

No

No

No

No

Logistical context

Fleet deployment

Set covering

Pickup and delivery

Fixed route

Fleet deployment

Fleet deployment

Fleet deployment

Size of fleet

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Add more ships an option

No

No

No

Yes

No

Yes

Yes

Inventory costs included

No

No

No

No

Yes

No

No

Emissions considered

No

Yes

No

No

No

No

No

Modal split considered

No

No

No

No

No

No

No

Ports included

 

No

No

Yes

Yes

No

No

Taxonomy part VI

Taxonomy parameter\ paper

Perakis and Papadakis (1987a, b)

Perakis and Papadakis (1989)

Psaraftis and Kontovas (2009b)

Psaraftis and Kontovas (2010)

Psaraftis and Kontovas (2014)

Qi and Song (2012)

Ronen (1982)

Optimization criterion

Cost

Time

Cost

Cost

Cost

Fuel consumption

Profit

Shipping market

Tramp

General

Tramp

General

General

liner

Tramp

Decision maker

Owner

Ship’s master

Charterer

Charterer

Charterer

Owner

Owner

Fuel price an explicit input

Yes

No

Yes

No

Yes

No

Yes

Freight rate an input

No

No

Input

Input

Input

No

Input

Fuel consumption function

General

N/A

Cubic

General

General

cubic

Cubic

Optimal speeds in various legs

Yes

N/A

Yes

No

Yes

Yes

Yes

Optimal speeds as function of payload

No

No

Yes

No

Yes

No

No

Logistical context

Fleet deployment

Weather routing

Fixed route

Fixed route

Fixed or flexible route

Scheduling

Fixed route

Size of fleet

Multiple ships

One ship

Multiple ships

Multiple ships

One ship

Multiple ships

One ship

Add more ships an option

No

No

Yes

Yes

No

No

No

Inventory costs included

Yes

No

Yes

Yes

Yes

No

No

Emissions considered

No

No

Yes

No

Yes

Yes

No

Modal split considered

No

No

No

Yes

No

No

No

Ports included

Yes

Yes

No

No

No

Yes

Yes

Taxonomy part VII

Taxonomy parameter\paper

Ronen (2011)

Stopford (2009)

Wang and Meng (2012a)

Wang and Meng (2012b)

Wang and Meng (2012c)

Wang et al. (2014)

Yao, Ng, and Lee (2012)

Optimization criterion

Cost

Profit

Cost

Total cost and fuel cost

Cost

Cost

Fuel cost

Shipping market

Container

General

Container

Liner

Liner

Container

Container

Decision maker

Owner

Owner

Owner

Owner

Owner

Owner

Owner

Fuel price an explicit input

Yes

Yes

Yes

Yes

Yes

Yes

Yes

Freight rate an input

No

Input/computed

No

No

No

No

No

Fuel consumption function

Cubic

Cubic

linearized

cubic

linearized

General

cubic

Optimal speeds in various legs

No

No

Yes

Yes

Yes

Yes

Yes

Optimal speeds as function of payload

No

No

No

No

No

No

No

Logistical context

Fixed route

Fixed route

Scheduling

Scheduling

Scheduling

Schedule design

Bunker fuel management

Size of fleet

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Multiple ships

Add more ships an option

Yes

No

No

No

No

No

No

Inventory costs included

No

Yes

No

No

No

Yes

No

Emissions considered

No

No

No

No

No

No

No

Modal split considered

No

No

No

No

No

No

No

Ports included

Yes

Yes

Yes

Yes

Yes

Yes

Yes

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Psaraftis, H.N., Kontovas, C.A. (2016). Green Maritime Transportation: Speed and Route Optimization. In: Psaraftis, H. (eds) Green Transportation Logistics. International Series in Operations Research & Management Science, vol 226. Springer, Cham. https://doi.org/10.1007/978-3-319-17175-3_9

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