Research on intelligent design method of ship multi-deck compartment layout based on improved taboo search genetic algorithm

2021 ◽  
Vol 225 ◽  
pp. 108823
Author(s):  
Yun-long Wang ◽  
Zhang-pan Wu ◽  
Guan Guan ◽  
Kai Li ◽  
Shu-hong Chai
2012 ◽  
Vol 472-475 ◽  
pp. 2235-2240 ◽  
Author(s):  
Tu Lan ◽  
Sheng Ju Tang ◽  
Bo Chen ◽  
De Ke Guo

Because of the outstanding advantages of genetic algorithms in solving optimization problems of engineering design, in this paper, using genetic algorithm combined with Kansei Engineering as a optimal design method for product’s semantics modeling design, and using real-coded way to characterize shape characteristics of CNC machine tools, comprehensive accounted of user’s semantic needs and color Mido, then, established the fitness function, combined with the key components to complete the design. By case analysis shows that the method is feasible, and lays a foundation for intelligent design of CNC machine tools.


2020 ◽  
Vol 54 (2) ◽  
pp. 79-92
Author(s):  
Yun-long Wang ◽  
Zhang-pan Wu ◽  
Guan Guan ◽  
Chao-guang Jin

AbstractThe design of the ship cabin layout is a multi-objective comprehensive optimization problem, which needs to consider the location of the passage, cabin layout, space utilization ratio, functional realization, comfort, safety, and so on. In this paper, an improved tabu-criterion genetic algorithm for the intelligent design of ship cabin layout is proposed. According to the characteristics of ship accommodation cabin layout design, a ship deck layout area model and a multi-objective optimization model including relative location model, absolute location model, and ergonomic constraint model are established. The neighborhood transformation criterion and tabu-criterion of tabu search algorithm are introduced into genetic algorithm to advance the local search ability of a genetic algorithm. At the same time, a new genetic algorithm coding method is proposed to avoid the generation of illegal solutions in cabin layout sequence crossover and mutation operation. The improved genetic algorithm can effectively improve the local search ability of a genetic algorithm and make the algorithm converge to the optimal solution as soon as possible at the later stage of calculation. Finally, the simulation results verify the feasibility and efficiency of the proposed intelligent design method for ship accommodation cabin layout.


2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Yingfeng Zhao ◽  
Jianhua Liu ◽  
Jiangtao Ma ◽  
Linlin Wu

AbstractCurrent studies on cable harness layouts have mainly focused on cable harness route planning. However, the topological structure of a cable harness is also extremely complex, and the branch structure of the cable harness can affect the route of the cable harness layout. The topological structure design of the cable harness is a key to such a layout. In this paper, a novel multi-branch cable harness layout design method is presented, which unites the probabilistic roadmap method (PRM) and the genetic algorithm. First, the engineering constraints of the cable harness layout are presented. An obstacle-based PRM used to construct non-interference and near to the surface roadmap is then described. In addition, a new genetic algorithm is proposed, and the algorithm structure of which is redesigned. In addition, the operation probability formula related to fitness is proposed to promote the efficiency of the branch structure design of the cable harness. A prototype system of a cable harness layout design was developed based on the method described in this study, and the method is applied to two scenarios to verify that a quality cable harness layout can be efficiently obtained using the proposed method. In summary, the cable harness layout design method described in this study can be used to quickly design a reasonable topological structure of a cable harness and to search for the corresponding routes of such a harness.


Author(s):  
John F. McGrew

This paper discusses a case study of a design and evaluation of a change management system at a large Telecommunications Corporation. The design and evaluation were done using the facilitated genetic algorithm (a parallel design method) and user decision style analysis. During the facilitated genetic algorithm the design team followed the procedure of the genetic algorithm. Usability was evaluated by applying user decision style analysis to the designed system. The design is compared with an existing system and with one designed by an analyst. The change management system designed by the facilitated genetic algorithm took less time to design and decision style analysis indicated it would be easier to use than the other two systems.


2013 ◽  
Vol 842 ◽  
pp. 695-702
Author(s):  
Ying Wang ◽  
You Rong Li ◽  
Yu Qiong Zhou

To enlarge production to meet the market demand, its nessasery to improve the present facility layout for MTO (Make-To-Order) manufacturing enterprises. This paper tries to design a optimization method based on genetic algorithm for the facility layout of MTO enterprises. Firstly, SLP (systematic layout planning) was applied to analyze the material and non-material flow interrelation of the workshop. Secondly, a relatively optimum layout was determined after using fuzzy hierarchy estimation to evaluate the schemes. Then the scheme was optimized with genetic algorithm. The result shows that the optimized logistics transport load is obviously less than before. This design method based on genetic algorithm (GA) is proved feasible and effective in the optimization of facility layout.


Author(s):  
Zhun Fan ◽  
Sofiane Achiche

The research work carried out in this paper introduces a robust design method for layout synthesis of MEM resonator subject to inherent geometric uncertainties such as the fabrication error on the sidewall of the structure. The robust design problem is formulated as a multi-objective constrained optimization problem with certain assumptions and treated by a special constrained genetic algorithm. The MEM design used for validation is a crab-leg resonator taken from the literature. The results show that the approach proposed in this research can lead to design results that meet the target performance and are less sensitive to geometric uncertainties than typical designs.


Author(s):  
Andrew J. Robison ◽  
Andrea Vacca

A gerotor gear generation algorithm has been developed that evaluates key performance objective functions to be minimized or maximized, and then an optimization algorithm is applied to determine the best design. Because of their popularity, circular-toothed gerotors are the focus of this study, and future work can extend this procedure to other gear forms. Parametric equations defining the circular-toothed gear set have been derived and implemented. Two objective functions were used in this kinematic optimization: maximize the ratio of displacement to pump radius, which is a measure of compactness, and minimize the kinematic flow ripple, which can have a negative effect on system dynamics and could be a major source of noise. Designs were constrained to ensure drivability, so the need for additional synchronization gearing is eliminated. The NSGA-II genetic algorithm was then applied to the gear generation algorithm in modeFRONTIER, a commercial software that integrates multi-objective optimization with third-party engineering software. A clear Pareto front was identified, and a multi-criteria decision-making genetic algorithm was used to select three optimal designs with varying priorities of compactness vs low flow variation. In addition, three pumps used in industry were scaled and evaluated with the gear generation algorithm for comparison. The scaled industry pumps were all close to the Pareto curve, but the optimized designs offer a slight kinematic advantage, which demonstrates the usefulness of the proposed gerotor design method.


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