Life Balance-Considered Matching Optimization Method for Remanufactured Parts

2020 ◽  
Vol 20 (4) ◽  
Author(s):  
Xuhui Xia ◽  
Shuping Wang ◽  
Zelin Zhang ◽  
Lei Wang ◽  
Yuan Gong
Keyword(s):  
Life Cycle ◽  
Ant Colony Algorithm ◽  
Optimization Method ◽  
Life Balance ◽  
Matching Process ◽  
Component Matching ◽  
Matching Degree ◽  
Full Utilization ◽  
Minimal Life ◽  
Improved Ant Colony Algorithm

Abstract In the manufacturing process of remanufactured products, balancing the life between their components is one of the important measures to achieve full utilization of waste components and sustainable economic development. In order to prolong the life cycle of remanufactured products and increase the life of parts and components, a life balance-considered matching optimization method is proposed for remanufactured parts in the process of components matching. By comprehensively considering the life matching degree of remanufactured parts and the matching success rate, a life balance-considered matching optimization model is established for remanufactured parts. We adopted an improved ant colony algorithm to solve the proposed matching model to get multiple sets of optimal component combinations with minimal life deviations between component combinations. The correctness of the model and the effectiveness of the algorithm are verified by taking the gear reducer component matching process as an example.

scholarly journals Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm

Open Physics ◽  
2019 ◽  
Vol 17 (1) ◽  
pp. 48-59 ◽  
Author(s):  
Rong He ◽  
Xinli Wei ◽  
Nasruddin Hassan
Keyword(s):  
Performance Optimization ◽  
Ant Colony Algorithm ◽  
Optimal Solution ◽  
Second Law Of Thermodynamics ◽  
Optimization Method ◽  
Ant Colony ◽  
Multi Objective ◽  
Objective Performance ◽  
Performance Evaluation Index ◽  
Improved Ant Colony Algorithm

Abstract To solve the problem of multi-objective performance optimization based on ant colony algorithm, a multi-objective performance optimization method of ORC cycle based on an improved ant colony algorithm is proposed. Through the analysis of the ORC cycle system, the thermodynamic model of the ORC system is constructed. Based on the first law of thermodynamics and the second law of thermodynamics, the ORC system evaluation model is established in a MATLAB environment. The sensitivity analysis of the system is carried out by using the system performance evaluation index, and the optimal working parameter combination is obtained. The ant colony algorithm is used to optimize the performance of the ORC system and obtain the optimal solution. Experimental results show that the proposed multi-objective performance optimization method based on the ant colony algorithm for the ORC cycle needs a shorter optimization time and has a higher optimization efficiency.

An Information Classification Optimization Model Based on Improved Ant Colony Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 1989-1992 ◽  
Author(s):  
Chun Mei Hao
Keyword(s):  
Ant Colony Algorithm ◽  
Optimization Method ◽  
Ant Colony ◽  
Classification Model ◽  
Model Based ◽  
Information Classification ◽  
Information Optimization ◽  
Classification Information ◽  
Improved Ant Colony Algorithm

In the information management process, it is necessary to classify all information optimization to provide the support for quickly query the search target providing this, a classification optimization method based on improved ant colony algorithm is proposed in this paper. That is, extract the characteristics of information attribute, and then establish the optimization classification model based on the characteristics to achieve the classification of information. Experimental results show that using the improved algorithm for classification information, the classification accuracy can be improved to meet the actual demand data management.

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