Optimal Compartment Layout Design for a Naval Ship Using an Improved Genetic Algorithm

2002 ◽  
Vol 39 (03) ◽  
pp. 159-169
Author(s):  
Kyu-Yeul Lee ◽  
Seong-Nam Han ◽  
Myung-I Roh
Keyword(s):  
Genetic Algorithm ◽  
Design Procedure ◽  
Layout Design ◽  
Computational Results ◽  
Improved Genetic Algorithm ◽  
Layout Problem ◽  
Comparative Testing ◽  
Naval Ship ◽  
Space Layout ◽  
Better Than

With the trend in modern naval ships towards less dense payloads, space layout design has become more important. Recent advances in computing science and increased understanding of methods for developing mathematical models, which form the basis of the space layout design, have helped with the development of a powerful design procedure. In this study, the compartment layout problem, which can be regarded as the space layout design of a naval ship, is represented as a mathematical model, and a compartment layout algorithm based on the genetic algorithm (GA) in order to solve the problem is proposed. Comparative testing shows that the proposed algorithm performs better than other existing algorithms for the optimal compartment layout design. Finally, the proposed algorithm is applied to the compartment layout problem of a naval ship and the computational results are compared with the actual compartment layout of the naval ship.

scholarly journals OPTIMISATION OF NAVAL SHIP COMPARTMENT LAYOUT DESIGN USING GENETIC ALGORITHM

2021 ◽  
Vol 1 ◽  
pp. 2339-2348
Author(s):  
Venkata Aditya Dharani Pragada ◽  
Akanistha Banerjee ◽  
Srinivasan Venkataraman
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Layout Design ◽  
Test Case ◽  
Improved Genetic Algorithm ◽  
Search Technique ◽  
Layout Problem ◽  
General Arrangement ◽  
Naval Ship

AbstractAn efficient general arrangement is a cornerstone of a good ship design. A big part of the whole general arrangement process is finding an optimized compartment layout. This task is especially tricky since the multiple needs are often conflicting, and it becomes a serious challenge for the ship designers. To aid the ship designers, improved and reliable statistical and computation methods have come to the fore. Genetic algorithms are one of the most widely used methods. Islier's algorithm for the multi-facility layout problem and an improved genetic algorithm for the ship layout design problem are discussed. A new, hybrid genetic algorithm incorporating local search technique to further the improved genetic algorithm's practicality is proposed. Further comparisons are drawn between these algorithms based on a test case layout. Finally, the developed hybrid algorithm is implemented on a section of an actual ship, and the findings are presented.

Based on Improved Genetic Algorithm for Task Scheduling of Heterogeneous Multi-Core Processor

2014 ◽  
Vol 1030-1032 ◽  
pp. 1671-1675
Author(s):  
Yue Qiu ◽  
Jing Feng Zang
Keyword(s):  
Genetic Algorithm ◽  
Task Scheduling ◽  
Execution Time ◽  
Scheduling Algorithm ◽  
Experimental Results ◽  
Initial Population ◽  
Improved Genetic Algorithm ◽  
High Quality ◽  
Multi Core Processor ◽  
Better Than

This paper puts forward an improved genetic scheduling algorithm in order to improve the execution efficiency of task scheduling of the heterogeneous multi-core processor system and give full play to its performance. The attribute values and the high value of tasks were introduced to structure the initial population, randomly selected a method with the 50% probability to sort for task of individuals of the population, thus to get high quality initial population and ensured the diversity of the population. The experimental results have shown that the performance of the improved algorithm was better than that of the traditional genetic algorithm and the HEFT algorithm. The execution time of tasks was reduced.

An Improved Genetic Algorithm for Digital Facility Layout Optimization Oriented Multi-Species and Variable-Batch Production Mode

2013 ◽  
Vol 694-697 ◽  
pp. 3632-3635
Author(s):  
Dao Guo Li ◽  
Zhao Xia Chen
Keyword(s):  
Genetic Algorithm ◽  
Facility Layout ◽  
Optimal Solution ◽  
Convergence Speed ◽  
Improved Genetic Algorithm ◽  
Layout Problem ◽  
Batch Production ◽  
Production Mode ◽  
Slow Convergence ◽  
Weak Points

When solving facility layout problem for the digital workshop to optimize the production, the traditional genetic algorithm has its flaws with slow convergence speed and that the accuracy of the optimal solution is not ideal. This paper analyzes those weak points and proposed an improved genetic algorithm according to the characteristics of multi-species and variable-batch production mode. The proposed approach improved the convergence speed and the accuracy of the optimal solution. The presented model of GA also has been tested and verified by simulation.

The Study of Optimal Fuzzy PID-Smith Control Based on Genetic Algorithm

2013 ◽  
Vol 313-314 ◽  
pp. 448-452
Author(s):  
Dian Ting Liu ◽  
Hai Xia Li
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Control Method ◽  
Order System ◽  
Membership Functions ◽  
Fuzzy Pid ◽  
Improved Genetic Algorithm ◽  
Simulation Results ◽  
The Stability ◽  
Better Than

In this paper, the improved genetic algorithm is applied to optimize the quantization factors and the scaling factors of fuzzy control, and the optimized rule table and membership functions is obtained according to certain performances. Then a kind of optimal fuzzy PID-Smith control method based on genetic algorithm is proposed and its simulation model is built in this paper, a second-order system is simulated and analyzed. The results show that requirements of deterministic performances of the new control method are better than the conventional methods through the simulation results in the stability, rapidity and robustness.

Layout Design of Naval Gun Magazine Based on Improved GA

2009 ◽  
Vol 419-420 ◽  
pp. 669-672
Author(s):  
Wei Fu ◽  
Sheng Hai Hu ◽  
Yang Ge
Keyword(s):  
Genetic Algorithm ◽  
Optimization Model ◽  
System Reliability ◽  
Layout Design ◽  
Mutation Operator ◽  
Improved Genetic Algorithm ◽  
Encoding Scheme ◽  
Performance Constraints ◽  
Naval Gun ◽  
Polygon Method

In this paper a magazine layout optimization model with performance constraints is described and the objective function and its constraints of magazine layout are established. A multiobjective optimizations layout model based on polygon method is put forward. The model deals with a series of constraints such as geometry constraints, in-and-out point position optimization, magazine capacity and system reliability and safety. An improved genetic algorithm (GA) is proposed in this paper based on the new encoding scheme and logical mutation operator. The algorithm solved the problem of multiobjective layout design with performance constraints.

scholarly journals AN IMPROVED GENETIC ALGORITHM BASED FUZZY-TUNED NEURAL NETWORK

2005 ◽  
Vol 15 (06) ◽  
pp. 457-474 ◽  
Author(s):  
S. H. LING ◽  
F. H. F. LEUNG ◽  
H. K. LAM
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Neuron Model ◽  
Activation Functions ◽  
Improved Genetic Algorithm ◽  
Network Function ◽  
Fuzzy Network ◽  
Neural Fuzzy Network ◽  
Neural Fuzzy ◽  
Better Than

This paper presents a fuzzy-tuned neural network, which is trained by an improved genetic algorithm (GA). The fuzzy-tuned neural network consists of a neural-fuzzy network and a modified neural network. In the modified neural network, a neuron model with two activation functions is used so that the degree of freedom of the network function can be increased. The neural-fuzzy network governs some of the parameters of the neuron model. It will be shown that the performance of the proposed fuzzy-tuned neural network is better than that of the traditional neural network with a similar number of parameters. An improved GA is proposed to train the parameters of the proposed network. Sets of improved genetic operations are presented. The performance of the improved GA will be shown to be better than that of the traditional GA. Some application examples are given to illustrate the merits of the proposed neural network and the improved GA.

An Optimal Design Procedure of Wave Barriers for Mitigation of Underground and Above-Ground Railway Vibrations

2020 ◽  
Vol 20 (11) ◽  
pp. 2050121 ◽  
Author(s):  
Farbod Yarmohammadi ◽  
Reza Rafiee-Dehkharghani
Keyword(s):  
Genetic Algorithm ◽  
Design Procedure ◽  
Ground Surface ◽  
Fe Model ◽  
Optimal Layout ◽  
Analysis And Design ◽  
Different Types ◽  
Parallel Finite Element ◽  
Model Geometry ◽  
Better Than

In this paper, a robust parallel finite-element/genetic-algorithm (FE/GA) procedure is presented for finding the optimal layout of wave barriers in the ground alongside the underground or above-ground railways. The proposed FE/GA procedure is capable of optimizing the topology of the wave barriers by altering the FE model geometry and mesh at each optimization step to cope with the excitations by underground, above-ground, and simultaneous under- and above-ground loadings. The results obtained show that this coupled procedure is effective for the analysis and design of different types of wave barriers subjected to dynamic transient loadings. Three different types of wave barriers are studied including wave impeding blocks (WIBs), jet-grouted columns, and trenches. It is found that the open trenches have the largest mitigation capacity and if they cannot be used, the WIBs perform better than the jet-grouted columns. Although the wave barriers can notably reduce the ground vibrations induced by underground trains, they perform more effectively when the source of vibrations is located at the ground surface.

Using genetic algorithm to automate the generation of an open-plan office layout

2020 ◽  
pp. 147807712094353
Author(s):  
Chen Chen ◽  
Ricardo Jose Chacón Vega ◽  
Tiong Lee Kong
Keyword(s):  
Genetic Algorithm ◽  
Real Life ◽  
Layout Design ◽  
Algorithm Optimization ◽  
The Real ◽  
Office Design ◽  
Open Plan ◽  
Space Layout ◽  
A Minor ◽  
Nested Genetic Algorithm

Today, the concept of open plan is more and more widely accepted that many companies have switched to open-plan offices. Their design is an issue in the scope of space layout planning. Although there are many professional architectural layout design software in the market, in the real life, office designers seldom use these tools because their license fees are usually expensive and using them to solve an open-plan office design is like using an overly powerful and expensive tool to fix a minor problem. Therefore, manual drafting through a trial and error process is most often used. This article attempts to propose a lightweight tool to automate open-plan office layout generation using a nested genetic algorithm optimization with two layers, where the inner layer algorithm is embedded in the outer one. The result is enhanced by a local search. The main objective is to maximize space utilization by maximizing the size of the open workspace. This approach is different from its precedents, in that the location search is conducted on a grid map rather than several pre-selected candidate locations. Consequently, the generated layout design presents a less rigid workstation arrangement, inviting a casual and unrestrictive work environment. The real potential of the approach is reflected in the productivity of test fits. Automating and simplifying the generation of layouts for test fits can tremendously decrease the amount of time and resources required to generate them. The experimental case study shows that the developed approach is powerful and effective, making it a totally automated process.

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