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Multi-Objective Optimization in a Finite Time Thermodynamic Method for Dish-Stirling by Branch and Bound Method and MOPSO Algorithm

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Multi-Objective Optimization in a Finite Time Thermodynamic Method for Dish-Stirling by Branch and Bound Method and MOPSO Algorithm. / Nazemzadegan, Mohammad Raza; Kasaeian, Akibakhsh; Toghyani, Somayeh et al.
In: Frontiers in Energy, Vol. 14, 01.09.2020, p. 649–665.

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Nazemzadegan MR, Kasaeian A, Toghyani S, Ahmadi MH, Saidur R, Ming T. Multi-Objective Optimization in a Finite Time Thermodynamic Method for Dish-Stirling by Branch and Bound Method and MOPSO Algorithm. Frontiers in Energy. 2020 Sept 1;14:649–665. Epub 2018 Apr 6. doi: 10.1007/s11708-018-0548-0

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Nazemzadegan, Mohammad Raza ; Kasaeian, Akibakhsh ; Toghyani, Somayeh et al. / Multi-Objective Optimization in a Finite Time Thermodynamic Method for Dish-Stirling by Branch and Bound Method and MOPSO Algorithm. In: Frontiers in Energy. 2020 ; Vol. 14. pp. 649–665.

Bibtex

@article{78b2ea52072a4921971dbb17936795d5,
title = "Multi-Objective Optimization in a Finite Time Thermodynamic Method for Dish-Stirling by Branch and Bound Method and MOPSO Algorithm",
abstract = "There are various analyses for a solar system with the dish Stirling technology. One of those analyses is the finite time thermodynamic analysis. By the finite time thermodynamic analysis, the total power of system can be obtained by calculating the process time. In this study, the convection and radiation heat transfer losses from collector surface, the conduction heat transfer between hot and cold cylinders and cold side heat exchanger have been considered. During this investigation, the four objective functions have been optimized simultaneously. These objective functions are included of the power, efficiency, entropy and economic factors. In addition to the four-objective optimization, three-objective, two-objective and single-objective optimizations have been done on the dish-Stirling model. In this study, the algorithm of MOPSO with post-expression of preferences is used for multi-objective optimizations while the Branch and Bound algorithm with Pre-expression of preferences is used for single-objective and multi-objective optimizations. In case of multi-objective optimizations with post-expression of preferences, Pareto optimal front are obtained, afterward by implementing the Fuzzy, LINMAP and TOPSIS decision making algorithms, the single optimum results can be achieved. At the end, the comparison of the results shows the benefits of MOPSO in optimizing dish Stirling finite timethermodynamic equations. ",
keywords = "dish-Stirling, finite time model, branch and bound algorithm, multi-objective particle swarm optimization (MOPSO)",
author = "Nazemzadegan, {Mohammad Raza} and Akibakhsh Kasaeian and Somayeh Toghyani and Ahmadi, {Mohammad H.} and Rahman Saidur and Tingzhen Ming",
year = "2020",
month = sep,
day = "1",
doi = "10.1007/s11708-018-0548-0",
language = "English",
volume = "14",
pages = "649–665",
journal = "Frontiers in Energy",
issn = "2095-1701",
publisher = "Springer",

}

RIS

TY - JOUR

T1 - Multi-Objective Optimization in a Finite Time Thermodynamic Method for Dish-Stirling by Branch and Bound Method and MOPSO Algorithm

AU - Nazemzadegan, Mohammad Raza

AU - Kasaeian, Akibakhsh

AU - Toghyani, Somayeh

AU - Ahmadi, Mohammad H.

AU - Saidur, Rahman

AU - Ming, Tingzhen

PY - 2020/9/1

Y1 - 2020/9/1

N2 - There are various analyses for a solar system with the dish Stirling technology. One of those analyses is the finite time thermodynamic analysis. By the finite time thermodynamic analysis, the total power of system can be obtained by calculating the process time. In this study, the convection and radiation heat transfer losses from collector surface, the conduction heat transfer between hot and cold cylinders and cold side heat exchanger have been considered. During this investigation, the four objective functions have been optimized simultaneously. These objective functions are included of the power, efficiency, entropy and economic factors. In addition to the four-objective optimization, three-objective, two-objective and single-objective optimizations have been done on the dish-Stirling model. In this study, the algorithm of MOPSO with post-expression of preferences is used for multi-objective optimizations while the Branch and Bound algorithm with Pre-expression of preferences is used for single-objective and multi-objective optimizations. In case of multi-objective optimizations with post-expression of preferences, Pareto optimal front are obtained, afterward by implementing the Fuzzy, LINMAP and TOPSIS decision making algorithms, the single optimum results can be achieved. At the end, the comparison of the results shows the benefits of MOPSO in optimizing dish Stirling finite timethermodynamic equations.

AB - There are various analyses for a solar system with the dish Stirling technology. One of those analyses is the finite time thermodynamic analysis. By the finite time thermodynamic analysis, the total power of system can be obtained by calculating the process time. In this study, the convection and radiation heat transfer losses from collector surface, the conduction heat transfer between hot and cold cylinders and cold side heat exchanger have been considered. During this investigation, the four objective functions have been optimized simultaneously. These objective functions are included of the power, efficiency, entropy and economic factors. In addition to the four-objective optimization, three-objective, two-objective and single-objective optimizations have been done on the dish-Stirling model. In this study, the algorithm of MOPSO with post-expression of preferences is used for multi-objective optimizations while the Branch and Bound algorithm with Pre-expression of preferences is used for single-objective and multi-objective optimizations. In case of multi-objective optimizations with post-expression of preferences, Pareto optimal front are obtained, afterward by implementing the Fuzzy, LINMAP and TOPSIS decision making algorithms, the single optimum results can be achieved. At the end, the comparison of the results shows the benefits of MOPSO in optimizing dish Stirling finite timethermodynamic equations.

KW - dish-Stirling

KW - finite time model

KW - branch and bound algorithm

KW - multi-objective particle swarm optimization (MOPSO)

U2 - 10.1007/s11708-018-0548-0

DO - 10.1007/s11708-018-0548-0

M3 - Journal article

VL - 14

SP - 649

EP - 665

JO - Frontiers in Energy

JF - Frontiers in Energy

SN - 2095-1701

ER -