A hybrid method of modified NSGA-II and TOPSIS to optimize performance and emissions of a diesel engine using biodiesel

Etghani, Mir Majid; Shojaeefard, Mohammad Hassan; Khalkhali, Abolfazl; Akbari, Mostafa

doi:10.1016/j.applthermaleng.2013.05.041

Cited by 126 publications

(50 citation statements)

References 16 publications

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“…17 The basic concept of TOPSIS finds the positive ideal solution (S + ) as well as the negative ideal solution (S -), and then determines the best compromise solution, which is the closest to S + and the farthest from S -, from the Pareto optimal solution according to the decision maker's objective weights. The detailed algorithm is presented in our pervious works.…”

Section: Multi-objective Optimizationmentioning

confidence: 99%

Multi objective optimization of friction stir welding parameters using FEM and neural network

Shojaeefard

Akbari

Asadi

2014

Int. J. Precis. Eng. Manuf.

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In this study the inuence of rotational and traverse speed on the friction stir welding of AA5083 aluminum alloy has been investigated. For this purpose a thermo-mechanically coupled, 3D FEM analysis was used to study the effect of rotational and traverse speed on welding force, peak temperature and HAZ width. Then, an Articial Neural Network (ANN) model was employed to understand the correlation between the welding parameters (rotational and traverse speed) and peak temperature, HAZ width and welding force values in the weld zone. Performance of the ANN model was found excellent and the model can be used to predict peak temperature, HAZ width and welding force. Furthermore, in order to find optimum values of traverse and rotational speed, the multi-objective optimization was used to obtain the Pareto front. Finally, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) was employed to obtain the best compromised solution.

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Section: Multi-objective Optimizationmentioning

confidence: 99%

Multi objective optimization of friction stir welding parameters using FEM and neural network

Shojaeefard

Akbari

Asadi

2014

Int. J. Precis. Eng. Manuf.

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“…In other words, it requires the decision or problem to be well structured. The TOPSIS algorithm steps can be classified as follows [9][10][11]:…”

Section: Topsis Methodsmentioning

confidence: 99%

TOPSIS Multi-Criteria Decision Modeling Approach for Biolubricant Selection for Two-Stroke Petrol Engines

et al. 2015

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Exhaust pollutants from two-stroke petrol engines are a problem for the environment. Biolubricants are a new generation of renewable and eco-friendly vegetable-based lubricants, which have attracted a lot of attention in recent years. In this paper, the applicability of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to support the process of building the scoring system for selecting an appropriate two-stroke lubricant has been analyzed. For this purpose, biolubricants (TMP-triesters) based on castor oil, palm oil, and waste cooking oil were produced and then utilized in a 200 cc two-stroke gasoline engine to investigate their effects on its performance and exhaust emissions. The results obtained from the use of the entropy technique in the TOPSIS algorithm showed that palm oil-based lubricant took up the greatest distance from the Negative Ideal Solution (NIS) and was selected as the most optimal lubricant for these types of engines.

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“…However, the multi-objective optimization algorithm must consider the fact that there are many "best solutions", which modify the selection process. NSGA-II sorts individuals based on the non-domination rank and the crowding distance to ensure a high level of performance as well as good dispersion of results 41,[56][57][58][59] . Fig.…”

Section: Non-dominated Sorting Genetic Algorithm-ii (Nsga-ii)mentioning

confidence: 99%

Simulating and Optimizing Hydrogen Production by Low-pressure Autothermal Reforming of Natural Gas using Non-dominated Sorting Genetic Algorithm-II

Azarhoosh

Ebrahim

Pourtarah

2016

Chem. Biochem. Eng. Q.

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Conventional hydrogen production plants consist of natural gas steam reforming to CO+3H 2 on Ni catalysts in a furnace, water-gas shift reaction for converting CO into CO 2 and CO 2 absorption. A new alternative method for highly endothermic steam reforming is autothermal reforming (steam reforming with air input to the reactor) without the need for external heating. In this study, hydrogen production by autothermal reforming for fuel cells (base case) was simulated based on a heterogeneous and one-dimensional model. In addition, the effect of operating variables on the system behavior was studied. Finally, Pareto-optimal solutions for the maximum molar flow rate of the produced hydrogen and methane conversion were determined by NSGA-II. There was a huge increase in the produced hydrogen molar flow to the base case, which showed the importance of optimizing autothermal reformers for hydrogen production.

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A hybrid method of modified NSGA-II and TOPSIS to optimize performance and emissions of a diesel engine using biodiesel

Cited by 126 publications

References 16 publications

Multi objective optimization of friction stir welding parameters using FEM and neural network

Multi objective optimization of friction stir welding parameters using FEM and neural network

TOPSIS Multi-Criteria Decision Modeling Approach for Biolubricant Selection for Two-Stroke Petrol Engines

Simulating and Optimizing Hydrogen Production by Low-pressure Autothermal Reforming of Natural Gas using Non-dominated Sorting Genetic Algorithm-II

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