Search Results - (( java implication based algorithm ) OR ( exchange optimization _ algorithm ))

Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi M., Darus A.N., Yousefi M., Hooshyar D.

“…Algorithms; Constraint theory; Design; Entropy; Fins (heat exchange); Genetic algorithms; Heat exchangers; Particle swarm optimization (PSO); Thermodynamics; Compact heat exchanger; Engineering applications; Entropy generation minimization; Evolutionary algorithms (EAs); Inequality constraint; Multi stage; Plate-fin heat exchanger; Variable operating condition; Evolutionary algorithms…”

A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

“…Constrained optimization; Genetic algorithms; Heat exchangers; Pareto principle; Particle swarm optimization (PSO); Compact heat exchanger; Constraint handling strategies; Constraints handling; Multi objective algorithm; Non-dominated sorting genetic algorithm - ii; Trial-and-error procedures; Trial-and-error process; Weighted sum approaches; Multiobjective optimization…”

Integration of zero and sequential algorithm in shuffle exchange with Minus One Stage by Md Yunus, Nur Arzilawati, Othman, Mohamed, Mohd Hanapi, Zurina

“…This paper focused on comparing the algorithm based on shuffle exchange network connection to achieve the optimal routing time as well as the number of passes to route in a given permutation. …”
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems by Yousefi, M., Darus, A.N., Yousefi, M., Hooshyar, D.

“…The complicated task of design optimization of compact heat exchangers (CHEs) have been effectively performed by using evolutionary algorithms (EAs) in the recent years. …”
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HEAT EXCHANGER NETWORK SYNTHESIS AND OPTIMIZATION BY PINCH ANALYSIS AND DIFFERENTIAL EVOLUTION METHOD by NGO , THI PHUONG THUY

“…Synthesis of Heat Exchanger Network (HEN) and optimization is a comprehensive method to design the network of heat exchangers for efficient heat recovery by cost-effective manner. …”
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Optimization of neural network topology for prediction of outlet temperature of shell and tube heat exchanger: article by Amir Latif, Abdul Rashid, Abdullah, Zalizawati

“…Artificial Neural Network (ANN), is applied for nearly a decades in most industries for its ability to project the non-linear property of heat transfer rate. Training algorithms used in this experiment to optimize the heat exchanger are trainlm,trainbr and trainscg. …”
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Optimization of neural network topology for prediction of outlet temperature of shell and tube heat exchanger by Amir Latif,, Abdul Rashid

“…Artificial Neural Network (ANN), is applied for nearly a decades in most industries for its ability to project the non-linear property of heat transfer rate. Training algorithms used in this experiment to optimize the heat exchanger are trainlm,trainbr and trainscg. …”
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Enhancing Market-Based Scheduling Algorithm on Globally Distributed Web Servers Using Least Suitable Sealed Bid Technique by Al-Ewiwi, Mahmoud

“…These agents work cooperatively with each other through the Internet using message exchanging.An improved algorithm was implemented to decrease the amount of message exchanging between agents, which increased the performance of the system.…”
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Modelling and control of heat exchanger by using bio-inspired algorithm by Daud, Nur Atiqah

“…The main objective of this study is to obtain structural model using ARMAX equation and optimize the value of PID parameters. In this study, data from heat exchanger experiment was used to determine the parameter of ARMAX equation and by using GA and PSO, all the parameters were optimized. …”
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Determination Of Heat Transfer Coefficients In Heat Exchangers By Genetic Algorithm by Tan Boon Tat, Boon Tat

“…In this study, the scope is limited to Nusselt Number correlations in the plain tube concentric heat exchanger and brazed plate heat exchanger. However, the method has general applicability for other types of heat exchangers. …”
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The optimization of technical trading strategy using genetic algorithm approach / Khairunnisa Musa by Musa, Khairunnisa

“…Recently, the use of genetic algorithm for the optimization of technical trading strategies has been receiving a great deal of attention. …”
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AI-enhanced generative design for efficient heat exchangers in thermoelectric generators: revolutionizing waste heat recovery in thermoelectricity / Andrew Robert Martin Hughes ...... by Andrew, Robert Martin Hughes, Bhathal Singh, Baljit Singh, Remeli, Muhammad Fairuz, Peixer, Guilherme Fidelis, Ratan Singh, Wandeep Kaur

“…The low conversion efficiency of TEGs means only a small fraction of waste heat is utilized, posing challenges to their long-term viability. While Genetic Algorithms (GAs) have shown promise in optimizing heat exchanger designs, advanced methods like Non-dominated Sorting Genetic Algorithm II (NSGA-II) have yet to be fully applied for PFHE TEG design. …”
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A comprehensive review on the application of evolutionary computation in design optimization of plate-fin heat exchangers by Yousefi M., Yousefi M., Khaksar W., Ismail Alnaimi F.B., Darus A.N.

“…This review study presents the utilization of different evolutionary algorithms (EAs) for plate-fin heat exchanger (PFHE) design optimization in the last decade. …”

Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management by Julius, Beneoluchi Odili, M. N. M., Kahar, Noraziah, Ahmad, M., Zarina, Riaz, Ul Haq

“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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An Optimized PID Parameters for LFC in Interconnected Power Systems Using MLSL Optimization Algorithm by Najeeb, Mushtaq, Shahooth, Mohammed, Mohaisen, Arrak, Ramdan, Razali, Hamdan, Daniyal

“…In order to enhance the dynamic performance, the optimal parameters of the PID scheme which optimized by the proposed MLSL algorithm are compared with that one’s obtained by GA algorithm. …”
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Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm by Tan K.M., Ramachandaramurthy V.K., Yong J.Y.

Dynamic modelling of proton exchange membrane fuel cell system for electric bicycle / Azadeh Kheirandish by Azadeh, Kheirandish

“…Classical linear regression and artificial neural networks as the most popular and accurate algorithms have been optimized and used for modeling this system. …”
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Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

“…This paper presents a novel algorithm, which is based on Gravitational Search Algorithm (GSA), for multiobjective optimization problems. …”
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Heat exchanger network optimization using differential evolution with stream splitting by Thuy, N.T.P., Pendyala, R., Marneni, N.

“…This article introduces a new strategy for HEN optimization using differential evolution algorithm. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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