Improved Genetic Algorithm to Optimization Pattern in Traffic Network Layout Problem

2015 ◽  
pp. 138-149
Author(s):  
Yingying Duan ◽  
Kang Zhou ◽  
Wenbo Dong ◽  
Qinhong Fu
Keyword(s):  
Genetic Algorithm ◽  
Traffic Network ◽  
Improved Genetic Algorithm ◽  
Layout Problem ◽  
Network Layout

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.

scholarly journals An Improved Genetic Algorithm for the Large-Scale Rural Highway Network Layout

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Changxi Ma ◽  
Cunrui Ma ◽  
Qing Ye ◽  
Ruichun He ◽  
Jieyan Song
Keyword(s):  
Genetic Algorithm ◽  
Large Scale ◽  
Spanning Trees ◽  
Polynomial Algorithms ◽  
Improved Genetic Algorithm ◽  
Exchange Method ◽  
Geographically Dispersed ◽  
Network Layout ◽  
Highway Network ◽  
Rural Highway

For the layout problem of rural highway network, which is often characterized by a cluster of geographically dispersed nodes, neither the Prim algorithm nor the Kruskal algorithm can be readily applied, because the calculating speed and accuracy are by no means satisfactory. Rather than these two polynomial algorithms and the traditional genetic algorithm, this paper proposes an improved genetic algorithm. It encodes the minimum spanning trees of large-scale rural highway network layout with Prufer array, a method which can reduce the length of chromosome; it decodes Prufer array by using an efficient algorithm with time complexityo(n)and adopting the single transposition method and orthoposition exchange method, substitutes for traditional crossover and mutation operations, which can effectively overcome the prematurity of genetic algorithm. Computer simulation tests and case study confirm that the improved genetic algorithm is better than the traditional one.

scholarly journals Double Genes Improved Genetic Algorithm for Solving Two-Dimensional Rectangular Layout Problem

2021 ◽  
Vol 2138 (1) ◽  
pp. 012007
Author(s):  
Min Cui ◽  
Kun Yang ◽  
Xiangming Deng ◽  
Shuqing Lyu ◽  
Miaomiao Feng ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Genetic Diversity ◽  
Population Diversity ◽  
Utilization Rate ◽  
Two Dimensional ◽  
Improved Genetic Algorithm ◽  
Layout Problem ◽  
Double Mutation ◽  
Mutation Operators ◽  
Random Crossover

Abstract Two-dimensional rectangular layout is according to the number of rectangular pieces and the size of the area of the rectangular pieces into the plate. Depending on the iteration of population in genetic algorithm, better utilization rate of plate is obtained. However, due to the characteristics of vertical and horizontal rows of rectangular pieces, relying on the sequence of rectangular pieces alone as the gene cannot guarantee the genetic diversity of the population, and leads to premature algorithm. In view of the special characters of rectangular layout, Double Genes improved genetic algorithm is proposed according to the order of rectangular layout and its own placement characteristics. In order to improve population diversity, Angle genes were added on the basis of rectangular sequencing genes. In view of the particularity of double genes, double random crossover operators and double mutation operators are proposed to improve the population diversity and randomness of genetic algorithm. Experimental results show the effectiveness of the improved algorithm.

scholarly journals OPTIMIZATION OF ARCHITECTURAL LAYOUT BY THE IMPROVED GENETIC ALGORITHM

2005 ◽  
Vol 11 (1) ◽  
pp. 13-21 ◽  
Author(s):  
Romualdas Baušys ◽  
Ina Pankrašovaite
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Rate Of Convergence ◽  
Conceptual Design ◽  
Search Method ◽  
Evolutionary Search ◽  
Improved Genetic Algorithm ◽  
Layout Problem ◽  
Current Stage

In this paper we consider architectural layout problem that seeks to determine the layout of Units based on lighting, heating, available sizes and other objectives and constraints. For a conceptual design of architectural layout we present an approach based on evolutionary search method known as the genetic algorithms (GAs). However, the rate of convergence of GAs is often not good enough at their current stage. For this reason, the improved genetic algorithm is proposed. We have analysed and compared the performance of standard and improved genetic algorithm for architectural layout problem solutions and presented the results of performance.

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.

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