A multi-objective performance modelling framework for enabling self-optimisation of cellular network topology and configurations

2016 ◽  
Vol 27 (7) ◽  
pp. 1000-1015 ◽  
Author(s):  
Hasan Farooq ◽  
Ali Imran ◽  
Adnan Abu-Dayya
Keyword(s):  
Network Topology ◽  
Cellular Network ◽  
Performance Modelling ◽  
Multi Objective ◽  
Modelling Framework ◽  
Objective Performance

Monitoring Perioperative Services Using 3D Multi-Objective Performance Frontiers

2021 ◽  
Vol 45 (3) ◽  
Author(s):  
Andrea J. Elhajj ◽  
Donna M. Rizzo ◽  
Gary C. An ◽  
Jaideep J. Pandit ◽  
Mitchell H. Tsai
Keyword(s):  
Multi Objective ◽  
Objective Performance

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.

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