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Optimizing Ship Routing to Maximize Fleet Revenue at Danaos

Optimizing Ship Routing to Maximize Fleet Revenue at Danaos. Enver Ellialtıoğlu Ahmet Can Ersöz IE 479. Introduction. About Danaos Corporation * Leading international shipowner * Key player with more than 60 containerships * Millions of containers

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Optimizing Ship Routing to Maximize Fleet Revenue at Danaos

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  1. Optimizing Ship Routing to Maximize Fleet Revenue at Danaos Enver Ellialtıoğlu Ahmet Can Ersöz IE 479

  2. Introduction About Danaos Corporation * Leading international shipowner * Key player with more than 60 containerships * Millions of containers * Millions of miles to thousands of parts * Millions tons of fuel oil

  3. Introduction About ORISMA * Operations Research In Ship Management * Integration of - financial data - hydrodynamic models - weather condition

  4. Introduction Best ship chartering option Optimal Solution Saving Million Dollars

  5. Introduction Defining a Ship Routing Problem ORISMA’s Implementation ORISMA’s Development Demonstration of Results Breakthrough Innovation!!! The path that is followed by researchers:

  6. Problem Definition • Tradeoff between least-cost and faster voyage • Least cost voyage Low speed • Losing operational days • Less oil consumption • Faster voyage High speed • Gaining operational days • More oil consumption

  7. Problem Definition * Objective 1: • Optimization of the ship fleet (minimizing total idle time) -Scheduling -Choosing right voyage -Choosing right crew

  8. Problem Definition • Objective 2: • Fleetwide long-term revenue maximization • Oil consumption(weather conditions, speed, bunkering) • Operational cost at each part(employee, port cost)

  9. Problem Definition * To sum up problems are: • Which voyage, when and through which route? • Bunkering time and ports?

  10. ORISMA’s Development • Routing Cost Minimization • Routing Cost and Time Minimization • Optimal Bunkering • Minimize Idle Time Whenever Next Employment Is Not Fixed

  11. ORISMA’s Development

  12. ORISMA’s Development

  13. ORISMA’s Development

  14. ORISMA’s Development

  15. ORISMA Example

  16. ORISMA’s Implementation Lack of knowledge Resistance to change Lack of motivation Change Management Plan Continous Training(courses, one-to-one sessions)

  17. ORISMA’s Implementation * Fluctuations(Theoretical-Actual) Weight Assignment * Extraction of restricted areas Artificial Module

  18. Realized Benefits Time Savings: $1.3M Fuel Savings: $3.2M 2011:30 Vessels 2012:65 Vessels Profitability: 7-10% Carbon emissions, Safety, Satisfaction

  19. Additional Examples & Questioning No concern about ordering, selling and buying new ship Decision Variables that would be added in an extra formula: *Alvarez, J. Fernando, Panagiotis Tsilingiris, Erna S. Engebrethsen, and Nikolaos M. P. Kakalis. 2011. Robust Fleet Sizing and Deployment for Industrial and Independent Bulk Ocean Shipping Companies. INFOR 49 (2): 93-107.

  20. Additional Examples & Questioning No concern about ship is arrived or not! Additional constraint in the red rectangle: *MarielleChristiansen, KjetilFagerholt, David Ronen, (2004) Ship Routing and Scheduling: Status and Perspectives. Transportation Science 38(1):1-18. http://dx.doi.org/10.1287/trsc.1030.0036

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