Optimal Design of a Ship Multitasking Cabin Layout Based on the Interval Optimization Method

Abstract

Searching for the optimal cabin layout plan is an effective way to improve the efficiency of the overall design and reduce a ship’s operation costs. The multitasking states of a ship involve several statuses when facing different missions during a voyage, such as the status of the marine supply and emergency escape. The human flow and logistics between cabins will change as the state changes. An ideal cabin layout plan, which is directly impacted by the above-mentioned factors, can meet the different requirements of several statuses to a higher degree. Inevitable deviations exist in the quantification of human flow and logistics. Moreover, uncontrollability is present in the flow situation during actual operations. The coupling of these deviations and uncontrollability shows typical uncertainties, which must be considered in the design process. Thus, it is important to integrate the demands of the human flow and logistics in multiple states into an uncertainty parameter scheme. This research considers the uncertainties of adjacent and circulating strengths obtained after quantifying the human flow and logistics. Interval numbers are used to integrate them, a two-layer nested system of interval optimization is introduced, and different optimization algorithms are substituted for solving calculations. The comparison and analysis of the calculation results with deterministic optimization show that the conclusions obtained can provide feasible guidance for cabin layout scheme.

Keywords

Cabin layout / Multitasking states / Uncertainty parameters / Interval optimization / Human flow and logistics

References

[1] Cheng P, Hong YY, Lan H, Wen SL, Yu DC, Zhang LJ. Allocation of ESS by interval optimization method considering impact of ship swinging on hybrid PV/diesel ship power system. Applied Energy, 2016, 175: 158-167

[2] Dai JJ, Li DQ, Li GH, Li P, Zhang YL. Optimization of ship uncertainty and robust design based on interval analysis method. Ship Engineering, 2018, 40(7): 14-19 87

[3] Drira A, Pierreval H, Hajri-Gabouj S. Facility layout problems: a survey. Annual Reviews in Control, 2007, 31(2): 255-267

[4] Guo J, Du XP. Reliability analysis for multidisciplinary systems with random and interval variables. Aiaa Journal, 2008, 48(1): 82-91

[5] Guo H, Ishizaka A, Li JH, Shi LL, Wu XY, Zhang SC. Optimum design of ship cabin equipment layout based on SLP method and genetic algorithm. Mathematical Problems in Engineering, 2019, 2019: 1-14

[6] Han Y, Lin Y, Wang YL, Wang C. Intelligent layout optimization design of ship pipeline. Journal of Shanghai Jiaotong University, 2015, 49(4): 513-518

[7] Hani P, Henri P, Helene M. Integrating facility layout design and aisle structure in manufacturing systems: formulation and exact solution. European Journal of Operational Research, 2020, 290(2): 499-513

[8] Hou YH. Hull form uncertainty optimization design for minimum EEOI with influence of different speed perturbation types. Ocean Engineering, 2017, 140: 66-72

[9] Hou YH, Liang X, Jiang XH, Shi XH. Application of uncertainty optimization method in optimal design of ship type. Journal of Huazhong University Science and Technology (Natural Science Edition), 2016, 44(6): 72-77

[10] Hu Y, Jiang ZF, Wang J, Xiong ZG. Design optimization of interior cabin location layout of volumetric ships based on SLP and genetic algorithm. Chinese Ship Research, 2013, 8(5): 19-26

[11] Hu Y, Jiang ZF, Wang J, Xiong ZG. Optimization of ship cabin layout based on improved genetic algorithm. Chinese Ship Research, 2014, 9(1): 20-30

[12] Huang S, Hou YH, Hu YL, Wang WQ, Wang C. Optimization model of ship channel layout and its particle swarm algorithm. Journal of Wuhan University of Technology, 2012, 34(9): 52-56

[13] Huang S, Li X, Liao QM, Wang Y. Design method of multi-deck cabin distribution based on gravitational search algorithm. China New Communications, 2016, 11(3): 11-16 60

[14] Kirtley N. Fuzzy optimal general arrangements in naval surface ship design. Ship Technology Research, 2009, 56(3): 121-141

[15] Li FY, Li GY, Zheng G. Research on interval-based uncertain multi-objective optimization method. Journal of Solid Mechanics, 2010, 31(1): 86-93

[16] Li DQ, Jiang ZY, Zhao X. Research on ship multidisciplinary robust design optimization under multidimensional stochastic uncertainty. Marine Engineering, 2015, 37(11): 61-66

[17] Li K, Wang YL, Wei H, Wu ZP. Intelligent layout design of ship cabins based on tabu search algorithm. Journal of Huazhong University of Science Technology (Natural Science Edition), 2018, 46(6): 49-53 70

[18] Mani S, Mostafa Z, Parham A, Shamsodin SH. A new soft computing algorithm based on cloud theory for dynamic facility layout problem. RAIRO-Operations Research, 2021, 55: S2433-S2453

[19] Rahayuda IGS, Santiari NPL. Dijkstra and bidirectional Dijkstra on determining evacuation routes. Journal of Physics: Conference Series, 2021, 1803(1): 012018

[20] Wu HF. Shortest path algorithm—Dijkstra and Floyd algorithm. China New Communications, 2019, 21(2): 32-33

[21] Wu HF. Shortest path algorithm—Dijkstra and Floyd algorithm. China New Commun, 2019, 21(2): 32-33

[22] Zhang H. Application of multidisciplinary design optimization in ship design. Ship Science and Technology, 2015, 37(6): 87-91

[23] Zhang XR. Research on layout optimization of ship meal system based on SLP. Ship, 2015, 26(4): 39-42