Collaborative Manufacturing Resources Configuration Based on Summary Process Routes

2010 ◽  
Vol 97-101 ◽  
pp. 2707-2710
Author(s):  
Ying Ying Su ◽  
Jian Rong Wang ◽  
Wan Shan Wang
Keyword(s):  
Adaptive Control ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Configuration Model ◽  
Manufacturing Environment ◽  
Multi Objective ◽  
Collaborative Manufacturing ◽  
Manufacturing Resources ◽  
Improved Ant Colony Algorithm

Aiming at manufacturing resources configuration in collaborative manufacturing environment, configuration flow with process tasks decomposition based on improved ant colony algorithm was proposed. Process tasks were decomposed based on summary process routes of parts and a multi-objective configuration model to collaborative manufacturing resources configuration was built. Basic ant colony algorithm was improved for solving this model by the combination of adaptive control and pheromone update mechanism. Pheromone is in the range of a max-min interval based on ant colony algorithm with the maximal-minimal pheromone limit. Compared to basic ant colony algorithm, superiority of improved ant colony algorithm was revealed by simulation 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.

Dual Objective Multidimensional Parameter Optimization of Cam Curve Based on Improved Ant Colony Algorithm

2014 ◽  
Vol 1037 ◽  
pp. 357-362
Author(s):  
Zhen Jun He ◽  
Peng Xu ◽  
Jiang Xiao Liao
Keyword(s):  
Objective Function ◽  
Ant Colony Algorithm ◽  
Weight Coefficient ◽  
Ant Colony ◽  
Multidimensional Space ◽  
Profile Curve ◽  
Multi Objective ◽  
Cam Mechanism ◽  
Variable Weight ◽  
Improved Ant Colony Algorithm

By applying improved ant colony algorithm, this paper analyzed multi-objective design problem in optimal design of cam mechanism profile curve, which were then transformed into TSP problem, that is, multi-objective function minimization problem into TSP shortest path searching problem. For the multiple complex variables and target weight parameters in design, a concept of multidimensional space node in ant colony optimization path was proposed, converting multi-objective function with weight coefficient into a multidimensional space nodes (city).At the same time, improved ant colony algorithm, combined with genetic algorithm, was used to avoid optimization calculation falling into a locally optimal solution. Exemplified by dual objective function in cam mechanism profile curve design, this paper solved optimal value problem of dual objective optimization design involving the biggest fullness coefficient and minimum abrasion quantity of variable weight coefficient under the three-dimensional parameters n, m and w.

A New Method of Product Configuration for Customization System into Supply Chain

2011 ◽  
Vol 121-126 ◽  
pp. 3870-3874
Author(s):  
Xue Yan Sun ◽  
Xing Yu Jiang ◽  
Shi Jie Wang ◽  
Xin Min Zhang
Keyword(s):  
Supply Chain ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
New Method ◽  
Product Configuration ◽  
Configuration Model ◽  
Solution Quality ◽  
Complex Product ◽  
Product Configuration Model ◽  
Improved Ant Colony Algorithm

To establish the configuration relations of complex product in the process of customization into supply chain, a new method of product configuration based on polychromatic graph theory was put forward. Then the optimum product structure configuration mathematical model was got and the improved ant colony algorithm was employed to solve the problem. The results showed that the solution quality got by improved ant colony algorithm was better than the solution got by traditional ant colony algorithm, and the product configuration model can exactly present the configuration information, product attribute and assembly relation for complex product. The customization system offers a kind of new way to meet customers’ requirements that the customers are eager for consumption of varieties, small batch production, short cycle and high quality.

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