scholarly journals An Effective Integrated Metaheuristic Algorithm For Solving Engineering Problems

2020 ◽  
Author(s):  
Adis Alihodzic ◽  
Sead Delalić ◽  
Dzenan Gusic
Keyword(s):  
Metaheuristic Algorithm ◽  
Engineering Problems

scholarly journals Tuna Swarm Optimization: A Novel Swarm-Based Metaheuristic Algorithm for Global Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-22
Author(s):  
Lei Xie ◽  
Tong Han ◽  
Huan Zhou ◽  
Zhuo-Ran Zhang ◽  
Bo Han ◽  
...  
Keyword(s):  
Global Optimization ◽  
Foraging Behavior ◽  
Metaheuristic Algorithm ◽  
Friedman Test ◽  
Swarm Optimization ◽  
Wilcoxon Rank Sum Test ◽  
Engineering Problems ◽  
Cooperative Foraging ◽  
Simulation Results

In this paper, a novel swarm-based metaheuristic algorithm is proposed, which is called tuna swarm optimization (TSO). The main inspiration for TSO is based on the cooperative foraging behavior of tuna swarm. The work mimics two foraging behaviors of tuna swarm, including spiral foraging and parabolic foraging, for developing an effective metaheuristic algorithm. The performance of TSO is evaluated by comparison with other metaheuristics on a set of benchmark functions and several real engineering problems. Sensitivity, scalability, robustness, and convergence analyses were used and combined with the Wilcoxon rank-sum test and Friedman test. The simulation results show that TSO performs better compared to other comparative algorithms.

THE ROLE OF FINITE ELEMENT METHOD IN CIVIL ENGINEERING

2018 ◽  
Vol 5 (02) ◽  
Author(s):  
Er. Hardik Dhull
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Approximate Solution ◽  
Analytical Method ◽  
Civil Engineering ◽  
The Finite Element Method ◽  
Engineering Problems ◽  
Building Components ◽  
Element Method

The finite element method is a numerical method that is used to find solution of mathematical and engineering problems. It basically deals with partial differential equations. It is very complex for civil engineers to study various structures by using analytical method,so they prefer finite element methods over the analytical methods. As it is an approximate solution, therefore several limitationsare associated in the applicationsin civil engineering due to misinterpretationof analyst. Hence, the main aim of the paper is to study the finite element method in details along with the benefits and limitations of using this method in analysis of building components like beams, frames, trusses, slabs etc.

Geotechnical settings of volcanic residual soils and derived engineering problems in El Hierro Island (Spain)

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Fabiola Fernández-Baniela ◽  
Daniel Arias ◽  
Álvaro Rubio-Ordóñez
Keyword(s):  
Residual Soils ◽  
El Hierro ◽  
Engineering Problems

scholarly journals Scenario reduction methodologies under uncertainties for reservoir development purposes: distance-based clustering and metaheuristic algorithm

2021 ◽  
Author(s):  
Seyed Kourosh Mahjour ◽  
Antonio Alberto Souza Santos ◽  
Manuel Gomes Correia ◽  
Denis José Schiozer
Keyword(s):  
Flow Simulation ◽  
Reduction Process ◽  
Computational Time ◽  
Metaheuristic Algorithm ◽  
Dynamic Data ◽  
Scenario Reduction ◽  
Field Development ◽  
Data Usage ◽  
Simulation Process ◽  
Uncertainty Space

AbstractThe simulation process under uncertainty needs numerous reservoir models that can be very time-consuming. Hence, selecting representative models (RMs) that show the uncertainty space of the full ensemble is required. In this work, we compare two scenario reduction techniques: (1) Distance-based Clustering with Simple Matching Coefficient (DCSMC) applied before the simulation process using reservoir static data, and (2) metaheuristic algorithm (RMFinder technique) applied after the simulation process using reservoir dynamic data. We use these two methods as samples to investigate the effect of static and dynamic data usage on the accuracy and rate of the scenario reduction process focusing field development purposes. In this work, a synthetic benchmark case named UNISIM-II-D considering the flow unit modelling is used. The results showed both scenario reduction methods are reliable in selecting the RMs from a specific production strategy. However, the obtained RMs from a defined strategy using the DCSMC method can be applied to other strategies preserving the representativeness of the models, while the role of the strategy types to select the RMs using the metaheuristic method is substantial so that each strategy has its own set of RMs. Due to the field development workflow in which the metaheuristic algorithm is used, the number of required flow simulation models and the computational time are greater than the workflow in which the DCSMC method is applied. Hence, it can be concluded that static reservoir data usage on the scenario reduction process can be more reliable during the field development phase.

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