scholarly journals Multi-objective optimization for creating a low-carbon logistics system through community-based action

2015 ◽  
Vol 9 (5) ◽  
pp. JAMDSM0063-JAMDSM0063
Author(s):  
Yoshiaki SHIMIZU ◽  
Tatsuhiko SAKAGUCHI ◽  
Hiroki SHIMADA
Keyword(s):  
Low Carbon ◽  
Multi Objective Optimization ◽  
Community Based ◽  
Logistics System ◽  
Multi Objective

scholarly journals Research on Blank Optimization Design Based on Low-Carbon and Low-Cost Blank Process Route Optimization Model

2021 ◽  
Vol 13 (4) ◽  
pp. 1929
Author(s):  
Yongmao Xiao ◽  
Wei Yan ◽  
Ruping Wang ◽  
Zhigang Jiang ◽  
Ying Liu
Keyword(s):  
Optimization Model ◽  
Optimization Design ◽  
Design Method ◽  
Low Cost ◽  
Route Optimization ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Blank Design ◽  
Process Route

The optimization of blank design is the key to the implementation of a green innovation strategy. The process of blank design determines more than 80% of resource consumption and environmental emissions during the blank processing. Unfortunately, the traditional blank design method based on function and quality is not suitable for today’s sustainable development concept. In order to solve this problem, a research method of blank design optimization based on a low-carbon and low-cost process route optimization is proposed. Aiming at the processing characteristics of complex box type blank parts, the concept of the workstep element is proposed to represent the characteristics of machining parts, a low-carbon and low-cost multi-objective optimization model is established, and relevant constraints are set up. In addition, an intelligent generation algorithm of a working step chain is proposed, and combined with a particle swarm optimization algorithm to solve the optimization model. Finally, the feasibility and practicability of the method are verified by taking the processing of the blank of an emulsion box as an example. The data comparison shows that the comprehensive performance of the low-carbon and low-cost multi-objective optimization is the best, which meets the requirements of low-carbon processing, low-cost, and sustainable production.

Low-carbon product multi-objective optimization design for meeting requirements of enterprise, user and government

2015 ◽  
Vol 103 ◽  
pp. 747-758 ◽  
Author(s):  
Zhi-Zheng Xu ◽  
Yi-Shou Wang ◽  
Zhen-Ru Teng ◽  
Chong-Quan Zhong ◽  
Hong-Fei Teng
Keyword(s):  
Optimization Design ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Carbon Product ◽  
Multi Objective

scholarly journals Discovering Network Community Based on Multi-Objective Optimization

2014 ◽  
Vol 24 (8) ◽  
pp. 2062-2077 ◽  
Author(s):  
Fa-Liang HUANG ◽  
Shi-Chao ZHANG ◽  
Xiao-Feng ZHU
Keyword(s):  
Multi Objective Optimization ◽  
Community Based ◽  
Multi Objective ◽  
Network Community

scholarly journals Multi-Objective Optimization for Grinding Parameters of 20CrMnTiH Gear with Ceramic Microcrystalline Corundum

Materials ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1352 ◽  
Author(s):  
Shengyong Zhang ◽  
Genbao Zhang ◽  
Yan Ran ◽  
Zhichao Wang ◽  
Wen Wang
Keyword(s):  
Surface Roughness ◽  
Practical Significance ◽  
Grinding Wheel ◽  
Linear Regression Method ◽  
Grinding Process ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Grinding Parameters ◽  
The Impact

(1) The alloy material 20CrMnTiH is widely used in gear manufacturing, but difficult to process, and its quantity (efficiency) and quality (surface quality) are generally negative correlation indicators. As a difficult but realistic problem, it is of important practical significance to explore how to efficiently grind high-precision low-carbon alloy gear workpieces. (2) Firstly, the pixel method was applied to analyze the grinding principles and explore the grinding parameters—the grinding wheel speed and grinding wheel frame moving speed—as well as the feed rate, which impacts the grinding indicators. Secondly, based on the ceramic microcrystalline corundum grinding wheel and the 20CrMnTiH gear workpiece, controlled experiments with 28 groups of grinding parameters were conducted. Moreover, the impact curves of the grinding parameters on the grinding indicators—the grinding efficiency, grinding wheel life, and surface roughness—were obtained by the multiple linear regression method. Finally, the multi-objective optimization method was used to comprehensively optimize the grinding process. (3) Compared with the traditional grinding process, under optimized grinding parameters, the 20CrMnTiH gear workpieces have a lower surface roughness and a longer grinding wheel life, and require a shorter time to achieve grinding accuracy. (4) The grinding experiments showed that the grinding parameters are linearly related to the grinding indicators. The optimization results show that the precision, efficiency, and economy of the 20CrMnTiH gear grinding process have been improved via the comprehensive optimization of the grinding parameters.

Multi-objective Optimization for Performance, Cost and Carbon Tax of Low-carbon Product

2014 ◽  
Vol 13 (2) ◽  
pp. 278-285 ◽  
Author(s):  
Zhi-Zheng Xu ◽  
Zhen-Ru Teng ◽  
Chong-Quan Zhong ◽  
Zhi-Jie Liu ◽  
Xiao-Fan Ma
Keyword(s):  
Carbon Tax ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Carbon Product ◽  
Multi Objective

scholarly journals Reverse Logistics Location Based on Energy Consumption: Modeling and Multi-Objective Optimization Method

2021 ◽  
Vol 11 (14) ◽  
pp. 6466
Author(s):  
Lijun Chang ◽  
Honghao Zhang ◽  
Guoquan Xie ◽  
Zhenzhong Yu ◽  
Menghao Zhang ◽  
...  
Keyword(s):  
Facility Location ◽  
Carbon Emissions ◽  
Optimization Algorithm ◽  
Reverse Logistics ◽  
Low Carbon ◽  
Multi Objective Optimization ◽  
Low Carbon Economy ◽  
Logistics Network ◽  
Multi Objective ◽  
Carbon Economy

The low-carbon economy, as a major trend of global economic development, has been a widespread concern, which is a rare opportunity to realize the transformation of the economic way in China. The realization of a low-carbon economy requires improved resource utilization efficiency and reduced carbon emissions. The reasonable location of logistics nodes is of great significance in the optimization of a logistics network. This study formulates a double objective function optimization model of reverse logistics facility location considering the balance between the functional objectives of the carbon emissions and the benefits. A hybrid multi-objective optimization algorithm that combines a gravitation algorithm and a particle swarm optimization algorithm is proposed to solve this reverse logistics facility location model. The mobile phone recycling logistics network in Jilin Province is applied as the case study to verify the feasibility of the proposed reverse logistics facility location model and solution method. Analysis and discussion are conducted to monitor the robustness of the results. The results prove that this approach provides an effective tool to solve the multi-objective optimization problem of reverse logistics location.

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