A comparative study of several nature-inspired algorithms in steel deck floor system cost optimization

Abstract Steel deck floor systems can be considered as one of the main components of a structure. As technology advances, the role of optimization is used in many aspects of structural designs. Steel deck floor systems are one of many components that are usually optimized to look for its optimum cost but are still able to hold the structure. This study compares the performance of the particle swarm optimization (PSO), artificial bee colony (ABC), differential evolution (DE), and symbiotic organisms search (SOS), that categorized as nature-inspired algorithms, in the optimization of a steel deck floor system. The variables considered are the edge beams, interior beams, and the composite steel deck. The results show that the SOS gives the most optimum cost with a better average and a perfect success rate.

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A comparative study of several bio-inspired algorithms in cost optimization of cellular beams

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/907/1/012001 ◽

2021 ◽

Vol 907 (1) ◽

pp. 012001

Author(s):

A Tjahjono ◽

E J Wijayanti ◽

D Prayogo ◽

F T Wong

Keyword(s):

Cost Efficiency ◽

Cost Optimization ◽

Live Load ◽

Success Rates ◽

Dead Load ◽

Symbiotic Organisms Search ◽

Bee Colony ◽

Symbiotic Organisms ◽

Selection Of

Abstract Castellated beams are commonly used in steel construction. This study will focus on castellated beams with circular-shaped openings, which are known as cellular beams. Cost optimization of cellular beams is needed to maintain cost efficiency. The optimization considers the selection of a root beam, the diameter of holes, and the total number of holes in the beam as the variables. Four metaheuristic algorithms are used to optimize the design, namely, the particle swarm optimization (PSO), differential evolution (DE), symbiotic organisms search (SOS), and artificial bee colony (ABC). A four-meter span beam with a 50 kN point live load in the middle of the beam and a 5 kN/m uniformly-distributed dead load are taken as the case study. The results indicate that the SOS algorithm yields the best optimization results in terms of the average, consistency, and convergence behavior with a 30 out of 30 success rates.

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Implementasi Metode Metaheuristik Symbiotic Organisms Search Dalam Penentuan Tata Letak Fasilitas Proyek Konstruksi Berdasarkan Jarak Tempuh Pekerja

Jurnal Teknik Industri ◽

10.9744/jti.19.2.103-114 ◽

2018 ◽

Vol 19 (2) ◽

pp. 103 ◽

Cited By ~ 2

Author(s):

Doddy Prayogo ◽

Richard Antoni Gosno ◽

Richard Evander ◽

Sentosa Limanto

Keyword(s):

Particle Swarm Optimization ◽

Artificial Bee Colony ◽

Particle Swarm ◽

Swarm Optimization ◽

Symbiotic Organisms Search ◽

Bee Colony ◽

Teaching Learning Based Optimization ◽

Teaching Learning ◽

Symbiotic Organisms

Penelitian ini menyelidiki performa dari metode metaheuristik baru bernama symbiotic organisms search (SOS) dalam menentukan tata letak fasilitas proyek konstruksi yang optimal berdasarkan jarak tempuh pekerja. Dua buah studi kasus tata letak fasilitas digunakan untuk menguji akurasi dan konsistensi dari SOS. Sebagai tambahan, tiga metode metaheuristik lainnya, yaitu particle swarm optimization, artificial bee colony, dan teaching–learning-based optimization, digunakan sebagai pembanding terhadap algoritma SOS. Hasil simulasi mengindikasikan bahwa algoritma SOS lebih unggul serta memiliki karakteristik untuk menghasilkan titik konvergen lebih cepat jika dibandingkan dengan metode metaheuristik lainnya dalam proses optimasi tata letak fasilitas proyek konstruksi.

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A Comparative Study on Bio-Inspired Algorithms in Layout Optimization of Construction Site Facilities

Civil Engineering Dimension ◽

10.9744/ced.20.2.102-110 ◽

2018 ◽

Vol 20 (2) ◽

pp. 102 ◽

Cited By ~ 1

Author(s):

Doddy Prayogo ◽

Jessica Chandra Sutanto ◽

Hieronimus Enrico Suryo ◽

Samuel Eric

Keyword(s):

Optimization Problems ◽

Transportation Cost ◽

Layout Optimization ◽

Symbiotic Organisms Search ◽

Bee Colony ◽

Site Layout ◽

Critical Attention ◽

Engineering Problems ◽

Symbiotic Organisms ◽

Planning Problems

A good arrangement of site layout on a construction project is a fundamental component of the project’s efficiency. Optimization on site layout is necessary in order to reduce the transportation cost of resources or personnel between facilities. Recently, the use of bio-inspired algorithms has received considerable critical attention in solving the engineering optimization problem. These methods have consistently provided better performance than traditional mathematical-based methods to a variety of engineering problems. This study compares the performance of particle swarm optimization (PSO), artificial bee colony (ABC), and symbiotic organisms search (SOS) algorithms in optimizing site layout planning problems. Three real-world case studies of layout optimization problems have been used in this study. The results show that SOS has a better performance in comparison to the other algorithms. Thus, this study provides useful insights to construction practitioners in the industry who are involved in dealing with optimization problems

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A modified controller design based on symbiotic organisms search optimization for desalination system

Journal of Water Supply Research and Technology—AQUA ◽

10.2166/aqua.2019.162 ◽

2019 ◽

Vol 68 (5) ◽

pp. 337-345 ◽

Cited By ~ 11

Author(s):

Natwar S. Rathore ◽

V. P. Singh ◽

Bui Duc Hong Phuc

Keyword(s):

Fresh Water ◽

Controller Design ◽

Fitness Function ◽

Time Domain Analysis ◽

Multivariable Model ◽

Symbiotic Organisms Search ◽

Bee Colony ◽

Squared Error ◽

Search Optimization ◽

Symbiotic Organisms

Abstract Fresh water demand is growing drastically in many parts of the world. Desalination of seawater, brackish water, and waste water is one solution to meet the demands of fresh water. Currently, reverse osmosis (RO) desalination process is one of the best methods for the desalination process. In this study, a modified controller design is proposed for RO desalination system based on symbiotic organisms search (SOS) algorithm. A multivariable model of RO desalination plant is considered for experimentation. The RO system considered here is first decoupled using a simplified decoupling process to obtain two non-interacting loops. Then, a proportional-integral-derivative controller with second order derivative (PID-DD) scheme based on SOS algorithm is proposed for each loop to find optimal control parameters of the RO system. To design the PID-DD controller for each loop, integral of squared error (ISE) is considered as fitness function. Four other state-of-the-art optimization algorithms, namely, teacher-learner-based-optimization (TLBO), differential evolution (DE), particle swarm optimization (PSO), and artificial bee colony (ABC), algorithms are also tested for the considered system. To show competitiveness of the proposed SOS-based PID-DD controller, a comparative study based on time domain analysis is performed. Results show the SOS-based PID-DD controller is superior to other PID-DD controllers.

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An optimal production plan for cashew nuts community enterprise using metaheuristic algorithms

International Journal of Applied Metaheuristic Computing ◽

10.4018/ijamc.292514 ◽

2022 ◽

Vol 13 (1) ◽

pp. 0-0

Keyword(s):

Production Cycle ◽

Production Plan ◽

Data Set ◽

Optimal Production ◽

Symbiotic Organisms Search ◽

Holding Costs ◽

Predictive Skill ◽

Bee Colony ◽

Ant Lion Optimization ◽

Symbiotic Organisms

The proper production plan plays an important role in the cashew nuts market enterprise in order to reduce cost. This study aims to find the optimal production plan for cashew nuts using ant lion optimization (ALO), symbiotic organisms search (SOS), particle swarm optimization (PSO) and artificial bee colony algorithm (ABC). The novel objective function is introduced in this study. Three input data set, including production cost, holding cost and inventory quantity are investigated. The experiment cases consist of the frequency of production cycle time in January, February and March, respectively. As a results, four algorithms are available to estimate not only the proper production plan of cashew nuts but also an ability in reducing the inventory and the holding costs. In summary, the ALO algorithm provides better predictive skill than others for the cashew nuts production plan with the lowest RMSE value of 0.0913.

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Simultaneous Scheduling of Machines and AGVS in FMS by Using Symbiotic Organisms Search (SOS) Algorithm

International Journal for Research in Applied Science and Engineering Technology ◽

10.22214/ijraset.2017.11258 ◽

2017 ◽

Vol V (XI) ◽

pp. 1780-1790

Author(s):

Kommuri S Reddy

Keyword(s):

Symbiotic Organisms Search ◽

Symbiotic Organisms ◽

Simultaneous Scheduling

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An efficient binary chaotic symbiotic organisms search algorithm approaches for feature selection problems

The Journal of Supercomputing ◽

10.1007/s11227-021-03626-6 ◽

2021 ◽

Author(s):

Hekmat Mohmmadzadeh ◽

Farhad Soleimanian Gharehchopogh

Keyword(s):

Feature Selection ◽

Search Algorithm ◽

Symbiotic Organisms Search ◽

Selection Problems ◽

Symbiotic Organisms

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An enhanced symbiotic organisms search algorithm for design optimization of trusses with frequency constraints

Advances in Structural Engineering ◽

10.1177/13694332211026219 ◽

2021 ◽

pp. 136943322110262

Author(s):

Mohammad H Makiabadi ◽

Mahmoud R Maheri

Keyword(s):

Standard Deviation ◽

Optimization Problems ◽

Search Algorithm ◽

Metaheuristic Algorithms ◽

Minimum Mass ◽

Multiple Frequency ◽

Frequency Constraints ◽

Symbiotic Organisms Search ◽

Symbiotic Organisms ◽

Dynamic Frequency

An enhanced symbiotic organisms search (ESOS) algorithm is developed and presented. Modifications to the basic symbiotic organisms search algorithm are carried out in all three phases of the algorithm with the aim of balancing the exploitation and exploration capabilities of the algorithm. To verify validity and capability of the ESOS algorithm in solving general optimization problems, the CEC2014 set of 22 benchmark functions is first optimized and the results are compared with other metaheuristic algorithms. The ESOS algorithm is then used to optimize the sizing and shape of five benchmark trusses with multiple frequency constraints. The best (minimum) mass, mean mass, standard deviation of the mass, total number of function evaluations, and the values of frequency constraints are then compared with those of a number of other metaheuristic solutions available in the literature. It is shown that the proposed ESOS algorithm is generally more efficient in optimizing the shape and sizing of trusses with dynamic frequency constraints compared to other reported metaheuristic algorithms, including the basic symbiotic organisms search and its other recently proposed improved variants such as the improved symbiotic organisms search algorithm (ISOS) and modified symbiotic organisms search algorithm (MSOS).

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Development of Optimal Design Method for Steel Double-Beam Floor System Considering Rotational Constraints

Applied Sciences ◽

10.3390/app11073266 ◽

2021 ◽

Vol 11 (7) ◽

pp. 3266

Author(s):

Insub Choi ◽

Dongwon Kim ◽

Junhee Kim

Keyword(s):

Optimal Design ◽

Design Process ◽

Design Method ◽

Steel Beams ◽

High Gravity ◽

Double Beam ◽

Iterative Analysis ◽

Floor Systems ◽

Optimal Design Method ◽

Floor System

Under high gravity loads, steel double-beam floor systems need to be reinforced by beam-end concrete panels to reduce the material quantity since rotational constraints from the concrete panel can decrease the moment demand by inducing a negative moment at the ends of the beams. However, the optimal design process for the material quantity of steel beams requires a time-consuming iterative analysis for the entire floor system while especially keeping in consideration the rotational constraints in composite connections between the concrete panel and steel beams. This study aimed to develop an optimal design method with the LM (Length-Moment) index for the steel double-beam floor system to minimize material quantity without the iterative design process. The LM index is an indicator that can select a minimum cross-section of the steel beams in consideration of the flexural strength by lateral-torsional buckling. To verify the proposed design method, the material quantities between the proposed and code-based design methods were compared at various gravity loads. The proposed design method successfully optimized the material quantity of the steel double-beam floor systems without the iterative analysis by simply choosing the LM index of the steel beams that can minimize objective function while satisfying the safety-related constraint conditions. In particular, under the high gravity loads, the proposed design method was superb at providing a quantity-optimized design option. Thus, the proposed optimal design method can be an alternative for designing the steel double-beam floor system.

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