An application of fuzzy-AHP to ship operational energy efficiency measures

Abstract Lowering fuel consumption of ships has gained a great deal of attention in maritime industry with regards to both environmental and economic concerns. The potential for fuel economy in shipping ranging between 25% to 75% is possible by using existing technology and practices and technical improvements in the design of new ship. Despite the existence of many technology and design-based approaches, limitations of emerging these measures has led to discussions about the potential energy savings through operational changes. In this study, operational measures were examined within the scope of Ship Energy Efficiency Management Plan (SEEMP) adopted by International Maritime Organization (IMO). We applied the Analytic Hierarchy Process (Fuzzy-AHP) approach, one of multi-criteria decision making (MCDM) techniques, to prioritize the weight of each measure. Fuzzy AHP effectively reflects the vagueness of human thinking with interval values, and shows the relative importance of operational measures – which can be the fundamental decision making data for decision makers (ships' masters, operating companies and ship owners) – by providing a strategic approach to identify energy efficient solutions.

[1]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[2]  D. S. Vlachos,et al.  Simulated annealing for optimal ship routing , 2012, Comput. Oper. Res..

[3]  C. de Wit,et al.  Proposal for Low Cost Ocean Weather Routeing , 1990, Journal of Navigation.

[4]  Li Zhang,et al.  Determination of the Shortest Time Route Based on the Composite Influence of Multidynamic Elements , 2011 .

[5]  Philip J Ballou,et al.  Ship energy efficiency management requires a Total Solution approach , 2013 .

[6]  Qiang Meng,et al.  A note on liner ship fleet deployment , 2011 .

[7]  James J. Corbett,et al.  The effectiveness and costs of speed reductions on emissions from international shipping , 2009 .

[8]  Rolf Skjong,et al.  Determining a required energy efficiency design index level for new ships based on a cost-effectiveness criterion , 2010 .

[9]  Inge Norstad,et al.  Reducing fuel emissions by optimizing speed on shipping routes , 2010, J. Oper. Res. Soc..

[10]  T. Saaty,et al.  The Analytic Hierarchy Process , 1985 .

[11]  A. Rahimi Ghazikalayeh,et al.  Application of Fuzzy Hybrid Analytic Network Process in Equipment Selection of Open-Pit Metal Mines , 2013 .

[12]  Andreas Pitsillides,et al.  Key issues for the design and development of mobile commerce services and applications , 2005, Int. J. Mob. Commun..

[13]  Qiang Meng,et al.  Schedule Design and Container Routing in Liner Shipping , 2011 .

[14]  Gang Kou,et al.  Analytic network process in risk assessment and decision analysis , 2014, Comput. Oper. Res..

[15]  Peilin Zhou,et al.  Development of a novel forward dynamic programming method for weather routing , 2012 .

[16]  Inge Sandaas,et al.  Reductions in cost and greenhouse gas emissions with new bulk ship designs enabled by the Panama Canal expansion , 2013 .

[17]  Popi Konidari,et al.  A multi-criteria evaluation method for climate change mitigation policy instruments , 2007 .

[18]  Christos A. Kontovas,et al.  Speed models for energy-efficient maritime transportation: A taxonomy and survey , 2013 .

[19]  A. Nagoor Gani,et al.  A New Operation on Triangular Fuzzy Number for Solving Fuzzy Linear Programming Problem , 2012 .

[20]  Gerald G. Brown,et al.  Scheduling short-term marine transport of bulk products , 1998 .

[21]  Mikael Johansson,et al.  Barriers to improving energy efficiency in short sea shipping: an action research case study , 2014 .

[22]  Jong Wook Kim,et al.  Prioritizing the weights of hydrogen energy technologies in the sector of the hydrogen economy by using a fuzzy AHP approach , 2011 .

[23]  Günther Clauss,et al.  Robust Pareto-optimum routing of ships utilising deterministic and ensemble weather forecasts , 2010 .

[24]  Stefan Nickel,et al.  Liner Shipping Hub Network Design in a Competitive Environment , 2010 .

[25]  Hongrui Ma,et al.  Well-to-wake energy and greenhouse gas analysis of SOX abatement options for the marine industry , 2012 .

[26]  Christos A. Kontovas,et al.  Balancing the economic and environmental performance of maritime transportation , 2010 .

[27]  Y. Ilker Topcu,et al.  A multiple-criteria decision-making approach for the evaluation of retail location , 2006 .

[28]  Pierre Cariou,et al.  Is slow steaming a sustainable means of reducing CO2 emissions from container shipping , 2011 .

[29]  Caniato Giovanni,et al.  BOOSTING ENERGY EFFICIENCY , 2016 .

[30]  Gülçin Büyüközkan,et al.  A combined fuzzy AHP and fuzzy TOPSIS based strategic analysis of electronic service quality in healthcare industry , 2012, Expert Syst. Appl..

[31]  Jingjing Xu,et al.  CO2 Emission Comparison Between Direct and Feeder Liner Services: A Case Study of Asia–Europe Services Interfacing with the UK , 2012 .

[32]  Mihalis M. Golias,et al.  The Berth-Scheduling Problem , 2010 .

[33]  David Pisinger,et al.  Fleet deployment, network design and hub location of liner shipping companies , 2011 .

[34]  Mehmet Atlar,et al.  An experimental investigation of the effect of foul release coating application on performance, noise and cavitation characteristics of marine propellers , 2012 .

[35]  Kevin Cullinane,et al.  ECONOMIES OF SCALE IN LARGE CONTAINERSHIPS: OPTIMAL SIZE AND GEOGRAPHICAL IMPLICATIONS. , 2000 .

[36]  Mehmet Atlar,et al.  The development of foul-release coatings for seagoing vessels , 2003 .

[37]  H Lackenby.  The Thirty-Fourth Thomas Lowe Gray Lecture: Resistance of Ships, with Special Reference to Skin Friction and Hull Surface Condition: , 1962 .

[38]  Peter Hoffmann,et al.  Pathways to Low Carbon Shipping - Abatement Potential Towards 2030 , 2009 .

[39]  Umut Asan,et al.  Use of HFACS–FCM in fire prevention modelling on board ships , 2015 .

[40]  Gento Mogi,et al.  A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices , 2013 .

[41]  S. Calvert,et al.  A Dynamic System for Fuel Optimization Trans-Ocean , 1991, Journal of Navigation.

[42]  Anders Hammer Strømman,et al.  The importance of economies of scale for reductions in greenhouse gas emissions from shipping , 2012 .

[43]  Ronald W. Yeung,et al.  The optimization of ship weather-routing algorithm based on the composite influence of multi-dynamic elements , 2013 .

[44]  Qiang Meng,et al.  Liner ship fleet deployment with container transshipment operations , 2012 .

[45]  Wen-Chin Chen,et al.  A fuzzy AHP and BSC approach for evaluating performance of IT department in the manufacturing industry in Taiwan , 2008, Expert Syst. Appl..

[46]  David Ronen,et al.  The Effect of Oil Price on the Optimal Speed of Ships , 1982 .

[47]  A. Stromman,et al.  Reductions in greenhouse gas emissions and cost by shipping at lower speeds , 2011 .

[48]  Aie.  World Energy Outlook 2009 , 2000 .

[49]  Qiang Meng,et al.  Liner shipping service network design with empty container repositioning , 2011 .

[50]  Golam Kabir,et al.  Evaluation of customer oriented success factors in mobile commerce using fuzzy AHP , 2011 .

[51]  Shigenobu Kobayashi,et al.  A new weather-routing system that accounts for ship stability based on a real-coded genetic algorithm , 2011 .

[52]  Christos A. Kontovas,et al.  Speed Reduction as an Emissions Reduction Measure for Fast Ships , 2009 .

[53]  Atilla Incecik,et al.  Seafarers’ current awareness, knowledge, motivation and ideas towards Low Carbon – Energy Efficient operations , 2012 .

[54]  Ian Jenkinson,et al.  Selection of techniques for reducing shipping NOx and SOx emissions , 2012 .

[55]  Kjetil Fagerholt,et al.  Ship Routing and Scheduling: Status and Perspectives , 2004, Transp. Sci..

[56]  Victor N. Armstrong.  Vessel optimisation for low carbon shipping , 2013 .

[57]  Xiangtong Qi,et al.  Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times , 2012 .

[58]  Akio Imai,et al.  The container shipping network design problem with empty container repositioning , 2007 .

[59]  Qiang Meng,et al.  Sailing speed optimization for container ships in a liner shipping network , 2012 .

[60]  Richard Y. K. Fung,et al.  Berth allocation considering fuel consumption and vessel emissions , 2011 .

[61]  Orestis Schinas,et al.  Forecasting bunker prices; A nonstationary, multivariate methodology , 2014 .

[62]  M. Thring.  World Energy Outlook , 1977 .

[63]  Debabrata Sen,et al.  DEVELOPMENT OF A SHIP WEATHER-ROUTING ALGORITHM FOR SPECIFIC APPLICATION IN NORTH INDIAN OCEAN REGION , 2010 .

[64]  T. Notteboom,et al.  The effect of high fuel costs on liner service configuration in container shipping , 2009 .

[65]  Inge Norstad,et al.  Tramp ship routing and scheduling with speed optimization , 2011 .

[66]  S A Harvald.  PREDICTION OF POWER OF SHIPS , 1977 .

[67]  D. Chang.  Applications of the extent analysis method on fuzzy AHP , 1996 .

[68]  R. W. Lunnon,et al.  Optimization of Time Saving in Navigation Through an Area of Variable Flow , 1992 .

[69]  Geoffrey Swain,et al.  The development of microfouling on four commercial antifouling coatings under static and dynamic immersion , 2006 .

[70]  Ching Chin Chang,et al.  Energy conservation for international dry bulk carriers via vessel speed reduction , 2013 .

[71]  Qiang Meng,et al.  Optimal operating strategy for a long-haul liner service route , 2011, Eur. J. Oper. Res..

[72]  Cengiz Kahraman,et al.  Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey , 2004 .

[73]  T. Notteboom.  The Time Factor in Liner Shipping Services , 2006 .

[74]  Gerasimos Theotokatos,et al.  A computational study on the performance and emission parameters mapping of a ship propulsion system , 2015 .

[75]  Georgios K. D. Saharidis,et al.  The berth allocation problem: Optimizing vessel arrival time , 2009 .

[76]  D. Ronen,et al.  The effect of oil price on containership speed and fleet size , 2011, J. Oper. Res. Soc..

[77]  Chao Chung Ho,et al.  Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process. , 2011, Waste management.

[78]  Irina Gribkovskaia,et al.  Reducing emissions through speed optimization in supply vessel operations , 2013 .

[79]  Metin Celik,et al.  Multiple attribute decision-making solution to material selection problem based on modified fuzzy axiomatic design-model selection interface algorithm , 2010 .

[80]  Prasad K. Bhaskaran,et al.  Application of wave model for weather routing of ships in the North Indian Ocean , 2008 .

[81]  Mohamed Ahmed Abdel-Rahman Mosaad,et al.  Marine propeller roughness penalties , 1986 .

[82]  Aşkın Özdağoğlu,et al.  Comparison of AHP and Fuzzy AHP for the Multi-Criteria Decision Making Processes with Linguistic Evaluations , 2007 .

[83]  Bekir Sahin,et al.  Fault Tree Analysis of chemical cargo contamination by using fuzzy approach , 2015, Expert Syst. Appl..