An industrial area layout design methodology considering piping and safety using genetic algorithm

2017 ◽  
Vol 167 ◽  
pp. 23-31 ◽  
Author(s):  
Ruiqi Wang ◽  
Yan Wu ◽  
Yufei Wang ◽  
Xiao Feng
Keyword(s):  
Genetic Algorithm ◽  
Design Methodology ◽  
Industrial Area ◽  
Layout Design

scholarly journals Coupling Layout Optimization of Key Plant and Industrial Area

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 185
Author(s):  
Yan Wu ◽  
Siyu Xu ◽  
Huan Zhao ◽  
Yufei Wang ◽  
Xiao Feng
Keyword(s):  
Genetic Algorithm ◽  
Catalytic Cracking ◽  
Hybrid Algorithm ◽  
Industrial Area ◽  
Layout Design ◽  
Width Ratio ◽  
Total Cost ◽  
Length Width ◽  
The Relationship

Layout problems are an engineering task that heavily relies on project experience. During the design of a plant, various factors need to be considered. Most previous efforts on industrial layout design have focused on the arrangement of facilities in a plant. However, the area-wide layout was not thoroughly studied and the relationship between plant layout and area-wide layout was rarely mentioned. In this work, the key plant that has the greatest impact on the industrial area is figured out first, and then the coupling relationships between the key plant and the industrial area are studied by changing the occupied area and length-width ratio of the key plant. Both of them are achieved by changing the floor number. A hybrid algorithm involving the genetic algorithm (GA) and surplus rectangle fill algorithm (SRFA) is applied. Various constraints are considered to make the layout more reasonable and practical. In the case study, a refinery with 20 plants is studied and the catalytic cracking plant is found to be the key plant. After the retrofit, the total cost of the refinery is 1,806,100 CNY/a less than that before, which illustrates the effectiveness of the method.

scholarly journals Multi-Branch Cable Harness Layout Design Based on Genetic Algorithm with Probabilistic Roadmap Method

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Yingfeng Zhao ◽  
Jianhua Liu ◽  
Jiangtao Ma ◽  
Linlin Wu
Keyword(s):  
Genetic Algorithm ◽  
Topological Structure ◽  
Design Method ◽  
Route Planning ◽  
Layout Design ◽  
Structure Design ◽  
Prototype System ◽  
Cable Harness ◽  
Probabilistic Roadmap ◽  
Probabilistic Roadmap Method

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.

Optimum layout design of sewer networks by hybrid genetic algorithm

2020 ◽  
Vol 8 (2) ◽  
pp. 108-124
Author(s):  
Waqed Hammed Hassan ◽  
Zahra H. Attea ◽  
Safaa S. Mohammed
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Layout Design ◽  
Sewer Networks

scholarly journals Rancangan Tata Letak Fasilitas Produksi Produk Rehabilitasi Dengan Algoritma Genetika

2019 ◽  
Vol 16 (3) ◽  
pp. 73
Author(s):  
Steaven Leonardo Chandra ◽  
Theresia Sunarni ◽  
Kristoforus Jawa Bendi ◽  
Dominikus Budiarto
Keyword(s):  
Genetic Algorithm ◽  
Production System ◽  
Layout Design ◽  
Production Volume ◽  
Production Facility ◽  
Total Flow ◽  
Facility Layout Design ◽  
Machine Layout ◽  
Section Production ◽  
Optimal Machine

The layout of production facilities has a very important impact and interrelationship between facilities with each other to support the smoothness of the production process.Frequently the biggest problems in the production system are caused by unsystematic handling of materials. This study, applies a genetic algorithm to obtain a facility layout design (machine) optimally. Inputs from this study include machine numbers, machine dimensions, machine sequences in each section, production volume in each section, and flow frequency in each section. The output of this study is the machine layout with a minimum total flow cost. This study solved the case in the rehab product production facility at PT Shima Prima Utama which consisting of 16 machines and 29 components. The results of the study in this case are that the optimal machine placement sequence is 13, 3, 9, 15, 6, 10, 2, 12, 8, 16, 7, 1, 11, 5, 14 and 4 with a total flow cost of 197,434.

scholarly journals An intelligence optimization method based on crowd intelligence for IoT devices

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ke Wang ◽  
Zheming Yang ◽  
Bing Liang ◽  
Wen Ji
Keyword(s):  
Genetic Algorithm ◽  
Design Methodology ◽  
Rapid Development ◽  
Optimization Method ◽  
The Internet ◽  
Content Type ◽  
Communication Capacity ◽  
Iot Devices ◽  
Crowd Intelligence ◽  
The Internet Of Things

Purpose The rapid development of 5G technology brings the expansion of the internet of things (IoT). A large number of devices in the IoT work independently, leading to difficulties in management. This study aims to optimize the member structure of the IoT so the members in it can work more efficiently. Design/methodology/approach In this paper, the authors consider from the perspective of crowd science, combining genetic algorithms and crowd intelligence together to optimize the total intelligence of the IoT. Computing, caching and communication capacity are used as the basis of the intelligence according to the related work, and the device correlation and distance factors are used to measure the improvement level of the intelligence. Finally, they use genetic algorithm to select a collaborative state for the IoT devices. Findings Experimental results demonstrate that the intelligence optimization method in this paper can improve the IoT intelligence level up to ten times than original level. Originality/value This paper is the first study that solves the problem of device collaboration in the IoT scenario based on the scientific background of crowd intelligence. The intelligence optimization method works well in the IoT scenario, and it also has potential in other scenarios of crowd network.

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