Optimum redundancy allocation using spider monkey optimization

Constraint optimization redundancy allocation problem (CoRAP) is a real-world, complex integer programming problem. Many researchers have used a variety of techniques to solve CoRAP. In the last two decades, evolutionary algorithms have been used by researchers to handle a variety of complex problem...

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Vydané v:Soft computing (Berlin, Germany) Ročník 27; číslo 21; s. 15595 - 15608
Hlavní autori: Agrawal, Amrita, Garg, Deepika, Sethi, Rachita, Shrivastava, Avinash K.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.11.2023
Springer Nature B.V
Predmet:
Artificial Intelligence
Branch and bound methods
Computational Intelligence
Control
Diabetes
Engineering
Evolutionary algorithms
Genetic algorithms
Heuristic
Heuristic methods
Integer programming
Leadership
Mathematical Logic and Foundations
Mechatronics
Neural networks
Optimization
Optimization algorithms
Optimization techniques
Psychology
Redundancy
Reverse osmosis
Robotics
System reliability
Water treatment
Water treatment plants
Student psychology-based optimization (SPBO)
Reliability
Redundancy allocation problem (RAP)
Heuristic algorithm
Branch and bound method
Spider monkey optimization algorithm (SMO)
ISSN:1432-7643, 1433-7479
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Shrnutí:Constraint optimization redundancy allocation problem (CoRAP) is a real-world, complex integer programming problem. Many researchers have used a variety of techniques to solve CoRAP. In the last two decades, evolutionary algorithms have been used by researchers to handle a variety of complex problems. Among these, the spider monkey optimization algorithm (SMO), which focuses on the behavior of monkeys, is one of the most promising and recent developments by researchers. In addition, no work has been undertaken in the context of solving CoRAP for water treatment plants so far. This paper proposed an integer programming problem, CoRAP for water treatment reverse osmosis (RO) plants subject to a cost constraint. The spider monkey optimization technique is applied to optimize the redundant units of the components of the plant, due to which the overall system reliability is maximized. A review of spider monkey optimization applications and modifications are also presented to investigate its performance. The same problem is solved by the heuristic algorithm, the branch and bound method and student psychology-based optimization technique to compare performance. The simulation work of spider monkey optimization, heuristic algorithms and student psychology-based optimization is implemented using MATLAB and the results for the branch and bound method are obtained using LINGO software. The findings demonstrate the better performance of spider monkey optimization.
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ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-023-08746-0