scholarly journals A Modification of the Imperialist Competitive Algorithm with Hybrid Methods for Multi-Objective Optimization Problems

Symmetry ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 173
Author(s):  
Jianfu Luo ◽  
Jinsheng Zhou ◽  
Xi Jiang ◽  
Haodong Lv

This paper proposes a modification of the imperialist competitive algorithm to solve multi-objective optimization problems with hybrid methods (MOHMICA) based on a modification of the imperialist competitive algorithm with hybrid methods (HMICA). The rationale for this is that there is an obvious disadvantage of HMICA in that it can only solve single-objective optimization problems but cannot solve multi-objective optimization problems. In order to adapt to the characteristics of multi-objective optimization problems, this paper improves the establishment of the initial empires and colony allocation mechanism and empire competition in HMICA, and introduces an external archiving strategy. A total of 12 benchmark functions are calculated, including 10 bi-objective and 2 tri-objective benchmarks. Four metrics are used to verify the quality of MOHMICA. Then, a new comprehensive evaluation method is proposed, called “radar map method”, which could comprehensively evaluate the convergence and distribution performance of multi-objective optimization algorithm. It can be seen from the four coordinate axes of the radar maps that this is a symmetrical evaluation method. For this evaluation method, the larger the radar map area is, the better the calculation result of the algorithm. Using this new evaluation method, the algorithm proposed in this paper is compared with seven other high-quality algorithms. The radar map area of MOHMICA is at least 14.06% larger than that of other algorithms. Therefore, it is proven that MOHMICA has advantages as a whole.

2014 ◽  
Vol 997 ◽  
pp. 721-727 ◽  
Author(s):  
Liang Jiang ◽  
Ya Dong Zhu ◽  
Victor Jin ◽  
Li Jun Yu

The choice of evaluating indicator has a most important influence on the performance analysis and optimization of Organic Rankine-cycle (ORC) system. In this paper, the net output power of unit mass of exhaust gas (), the cycle exergy efficiency (), the total waste heat emissions () and the product of exchanger's area and total heat transfer coefficient () are selected as the four key indicators which can reflect the characteristics of ORC system. And then, a comprehensive evaluating indicator of ORC system performance () is obtained according to the theory of multi-objective optimization. Further, a comprehensive evaluation method of ORC system performance based on the multi-objective optimization is put forward in this paper. After that, this method is used to optimize the evaporation temperature which is considered as a key parameter of ORC system performance. According to researches, the results gained by using a single-objective optimization method with only one performance parameter as the indicator, cannot often take a global view of the ORC system performance and sometimes may lead to a deviation. Researches also show that increases firstly and then decreases with the increment of the evaporation temperature, and there exists a value of evaporation temperature to maximize . Through analysis and researches, it can be found that the comprehensive evaluation method of ORC system performance based on the multi-objective optimization provided in this paper gives a synthetic consideration to the requirements from high-efficiency, economy, thermodynamic perfection and environment protection. Moreover, by using this method, the ORC power generation system may be more likely to achieve the best comprehensive performance.


Author(s):  
Azadeh Maroufmashat ◽  
Farid Sayedin ◽  
Sourena Sattari

Photovoltaic-electrolyzer systems are one of the most promising alternatives for obtaining hydrogen from a renewable energy source. Determining size and the operational conditions are always a key issue while coupling directly renewable electricity sources to PEM electrolyzer. In this research, the multi objective optimization approach based on an imperialist competitive algorithm (ICA), which is employed to optimize the size and the operating conditions of a directly coupled photovoltaic (PV)-PEM electrolyzer. This allows the optimization of the system by considering two different objectives, including, minimization of energy transfer loss and maximization of hydrogen generation. Multi objective optimization of PV/EL system predicts a maximum hydrogen production of 7930 gr/yr for energy transfer loss of 16.48 kWh/yr and minimum energy transfer loss of 5.21 kWh/yr at a hydrogen production rate of 7760 gr/yr for a the given location and the PV module.


2016 ◽  
Vol 48 (11) ◽  
pp. 1823-1844 ◽  
Author(s):  
Najlawi Bilel ◽  
Nejlaoui Mohamed ◽  
Affi Zouhaier ◽  
Romdhane Lotfi

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