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Institution

Iran University of Science and Technology

EducationTehran, Iran
About: Iran University of Science and Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Control theory & Nonlinear system. The organization has 12917 authors who have published 24965 publications receiving 372013 citations. The organization is also known as: Governmental Technical Institute & Advanced Art College.


Papers
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Journal ArticleDOI
TL;DR: The ability of DLLME technique in the extraction of other organic compounds such as organochlorine pesticides, organophosphorus pesticides and substituted benzene compounds were studied.

2,959 citations

Journal ArticleDOI
TL;DR: In this article, the authors present an overview of the key requirements for the proton exchange membranes (PEM) used in fuel cell applications, along with a description of the membrane materials currently being used and their ability to meet these requirements.

1,715 citations

Journal ArticleDOI
TL;DR: The performance of the CS algorithm is further compared with various algorithms representative of the state of the art in the area and the optimal solutions obtained are mostly far better than the best solutions obtained by the existing methods.
Abstract: In this study, a new metaheuristic optimization algorithm, called cuckoo search (CS), is introduced for solving structural optimization tasks. The new CS algorithm in combination with Levy flights is first verified using a benchmark nonlinear constrained optimization problem. For the validation against structural engineering optimization problems, CS is subsequently applied to 13 design problems reported in the specialized literature. The performance of the CS algorithm is further compared with various algorithms representative of the state of the art in the area. The optimal solutions obtained by CS are mostly far better than the best solutions obtained by the existing methods. The unique search features used in CS and the implications for future research are finally discussed in detail.

1,701 citations

Journal ArticleDOI
TL;DR: The proposed KH algorithm, based on the simulation of the herding behavior of krill individuals, is capable of efficiently solving a wide range of benchmark optimization problems and outperforms the exciting algorithms.

1,556 citations

Journal ArticleDOI
TL;DR: A comparison of the results with those of other evolutionary algorithms shows that the proposed algorithm outperforms its rivals.
Abstract: This paper presents a new optimization algorithm based on some principles from physics and mechanics, which will be called Charged System Search (CSS). We utilize the governing Coulomb law from electrostatics and the Newtonian laws of mechanics. CSS is a multi-agent approach in which each agent is a Charged Particle (CP). CPs can affect each other based on their fitness values and their separation distances. The quantity of the resultant force is determined by using the electrostatics laws and the quality of the movement is determined using Newtonian mechanics laws. CSS can be utilized in all optimization fields; especially it is suitable for non-smooth or non-convex domains. CSS needs neither the gradient information nor the continuity of the search space. The efficiency of the new approach is demonstrated using standard benchmark functions and some well-studied engineering design problems. A comparison of the results with those of other evolutionary algorithms shows that the proposed algorithm outperforms its rivals.

1,147 citations


Authors

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Network Information
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202371
2022233
20212,309
20202,289
20191,915
20181,746