Inclusion of hybrid algorithm in optimal operations of liquefied natural gas transfer arm under uncertainty

References

• Aspen Environmental Group. 2005. International and national efforts to address the safety and security risks of importing liquefied natural gas: a compendium. Contract Report, Prepared for California Energy Commission, Contract No. 700-99-014, California. Available from: http://www.energy.ca.gov/ 2005publications/CEC-600-2005-002/CEC-600-2005-002. PDF.
   Google Scholar
• Eleye-Datubo AG. 2006. Integrated risk-based modelling to safety-critical marine and offshore applications [dissertation]. Liverpool (UK): Liverpool John Moores University.
   Google Scholar
• Godaliyadde D, Phylip-Jones G, Yang ZL, Batako AD, Wang J. 2009. An analysis of ship hull vibration failure data. J UK Saf Reliability Soc. 29(1):15–26.
   Google Scholar
• Liu L, Yang JB, Wang J, Sii HS. 2004. A safety-cost based design-decision support framework using fuzzy evidential reasoning approach. Intell Sensory Eval Part 1; p. 31–50.
   Google Scholar
• Liu L, Yang JB, Wang J, Sii HS. 2005. Engineering system safety analysis and synthesis using the fuzzy rule-based evidential reasoning approach. Qual Reliability Eng Int. 21(4):387–411.
   Web of Science ®Google Scholar
• Maritime Safety Agency. 1993. Formal safety assessment. MSC66 /14, Submitted by the United Kingdom to International Maritime Organization, Maritime Safety Committee, London (UK).
   Google Scholar
• Newell M. 2003. Safe transfer of LNG between a floating production or storage barge to a transportation vessel at an exposed offshore location. Proceedings of the Spring National Meeting; 30 March–3 April; New Orleans (LA): American Institute of Chemical Engineers (AIChE).
   Google Scholar
• Nova Scotia Department of Energy. 2005. Code of practice: liquefied natural gas facilities. Nova Scotia (Canada): Department of Energy, Halifax.
   Google Scholar
• Nwaoha TC, Yang Z, Wang J, Bonsall S. 2011a. Application of genetic algorithm (GA) to risk-based maintenance operations of liquefied natural gas (LNG) carrier systems. Proc Institution of Mech Eng Part E. 225(1):40–52.
   Google Scholar
• Nwaoha TC, Yang Z, Wang J, Bonsall S. 2011b. A new fuzzy evidential reasoning method for risk analysis and control of liquefied natural gas (LNG) carrier containment system. Proc Institution of Mech Eng Part M. 225(1):206–225.
   Google Scholar
• Nwaoha TC, Yang Z, Wang J, Bonsall S. 2013a. A fuzzy genetic algorithm approach for analysing maintenance cost of high risk liquefied natural gas (LNG) carrier systems under uncertainty. Proc IMarEST Part A. 12(2):57–73.
   Google Scholar
• Nwaoha TC, Yang Z, Wang J, Bonsall S. 2013b. Adoption of new advanced computational techniques to hazards ranking in LNG carrier operations. Ocean Eng. 72(1):31–44.
   Web of Science ®Google Scholar
• Pillay A, Wang J. 2003. Technology and safety of marine systems. Elsevier Ocean Engineering Book Series. Oxford (UK): Elsevier Science Ltd. Vol. 7, ISBN: 0 08 044148 3.
   Google Scholar
• Society of International Gas Tanker and Terminal Operators. 1997. Site selection and design of LNG ports and jetties. London (UK): Society of International Gas Tankers and Terminal Operators Ltd.
   Google Scholar
• Tang WH, Spurgeon K, Wu QH, Richardson, ZJ. 2004. An evidential reasoning approach to transformer condition assessments. IEEE Trans Power Delivery. 19(4):1696–1703.
   Web of Science ®Google Scholar
• Wang J. 1997. A subjective methodology for safety analysis of safety requirements specifications. IEEE Trans Fuzzy Syst. 5(3):418–430.
   Web of Science ®Google Scholar
• Wang J. 2000. A subjective modelling tool applied to formal ship safety assessment. Ocean Eng. 27(10):1019–1035.
   Web of Science ®Google Scholar
• Wang J, Trbojevic VM. 2007. Design for safety of marine and offshore systems. London (UK): Institute of Marine Engineering, Science and Technology.
   Google Scholar
• Wang J, Yang JB. 2001. A subjective safety based decision making approach for evaluation of safety requirements specifications in software development. Int J Saf Qual Reliability. 8(8):35–57.
   Google Scholar
• Wang J, Yang JB, Sen P. 1995. Safety analysis and synthesis using fuzzy set modelling and evidential reasoning. Reliability Eng Syst Saf. 47:103–118.
   Web of Science ®Google Scholar
• Wang J, Yang JB, Sen P. 1996. Multi-person and multi-attribute design evaluations evidential reasoning based on subjective safety and cost analyses. Reliability Eng Syst Saf. 52(2):113–128.
   Web of Science ®Google Scholar
• Yang JB. 2001. Rule and utility based evidential reasoning approach for multi-attribute decision analysis under uncertainties. Eur J Oper Res. 131(1):31–61.
   Web of Science ®Google Scholar
• Yang Z, Bonsall S, Wall A, Wang J. 2005a. Reliable container supply chains – a new risk assessment framework for improving safety performance. J World Maritime Univ. 4(1):105–120.
   Google Scholar
• Yang JB, Sen P. 1997. Multiple attribute design evaluation of complex engineering products using the evidential reasoning approach. J Eng Des. 8(3):211–230.
   Web of Science ®Google Scholar
• Yang JB, Singh MG. 1994. An evidential reasoning approach for multiple attribute decision analysis with uncertainty. IEE Trans Syst Man Cybernetic. 24(1):1–18.
   Web of Science ®Google Scholar
• Yang Z, Wang J, Bonsall S, Fang Q, Yang JB. 2005b. A subjective risk analysis approach for container supply chains. Int J Autom Comput. 2(1):85–92.
   Google Scholar
• Yang JB, Xu DL. 2000. Intelligent decision system via evidential reasoning, version 1.1. Cheshire (England): IDSL.
   Google Scholar
• Yang JB, Xu DL. 2002. On the evidential reasoning algorithm for multiple attribute decision analysis under uncertainty. IEE Trans Syst Man Cybernetic- Part A. 32(3):289–304.
   Web of Science ®Google Scholar
• Zadeh LA. 1965. Fuzzy set. Inf Control. 8:338–353.
   Web of Science ®Google Scholar