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Showing 2 results for Sedaghat Shayegan

D. Sedaghat Shayegan, A Lork, S.a.h. Hashemi,
Volume 9, Issue 3 (6-2019)

In this paper, the optimum design of a reinforced concrete one-way ribbed slab, is presented via recently developed metaheuristic algorithm, namely, the Mouth Brooding Fish (MBF). Meta-heuristics based on evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques. The MBF algorithm simulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. This algorithm uses the movement, dispersion and protection behavior of Mouth Brooding Fish as a pattern to find the best possible answer. The cost of the system is considered to be the objective function, and the design is based on the American Concrete Institute’s ACI 318-08 standard. The performance of this algorithm is compared with harmony search (HS), colliding bodies optimization (CBO), particle swarm optimization (PSO), democratic particle swarm optimization (DPSO), charged system search (CSS) and enhanced charged system search (ECSS). The numerical results demonstrate that the MBF algorithm is able to construct very promising results and has merits in solving challenging optimization problems.
A. A. Saberi, D. Sedaghat Shayegan,
Volume 11, Issue 4 (11-2021)

Optimization has always been a human concern from ancient times to the present day, also in light of advances in computing equipment and systems, optimization techniques have become increasingly important in different applications. The role of metaheuristic algorithms in optimizing and solving engineering problems is expanding every day, optimization has also had many applications in water engineering. Every year, the effects of climate change and the water crisis deepen and worsen in many parts of the world, and existing water management becomes much more vital and critical. One of the main centers for water management and control dams reservoirs. In this paper, applying the CBO metaheuristic algorithm, the results of optimization in the operation of the Haraz dam reservoir in northern Iran, which has previously been done with FA and GA algorithms and standard operation system (SOP), are reviewed and compared. With the implementation of the CBO algorithm, all results and key outputs such as program runtime, annual water shortages, and vulnerabilities are much better than previous calculations, all the results are mentioned in the text of the article, but for example, the annual water shortage has reached about 38% of the FA algorithm, about 25% of the GA algorithm and about 13% of the SOP method. The numerical results demonstrate that the CBO algorithm has merits in solving challenging optimization problems and using this innovative algorithm can be an important starting point in the operation of dam reservoirs around the world.

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