OPTIMASI BIAYA PONDASI SETEMPAT DENGAN METODE METAHEURISTIK

2020 ◽  
Vol 7 (2) ◽  
pp. 47-52
Author(s):  
Vania Regina Husada ◽  
Ferdian Nathanael ◽  
Doddy Prayogo ◽  
Yudas Tadeus Teddy Susanto
Keyword(s):  
Particle Swarm Optimization ◽  
Bearing Capacity ◽  
Limit State ◽  
Ultimate Limit State ◽  
Swarm Optimization ◽  
Symbiotic Organisms Search ◽  
Serviceability Limit State ◽  
Capacity Theory ◽  
Symbiotic Organisms ◽  
Ultimate Limit

Pondasi adalah bagian dari struktur bangunan yang berfungsi meneruskan beban struktur atas ke lapisan tanah dengan aman. Sementara pondasi dangkal digunakan apabila lapisan tanah keras terletak dekat dengan permukaan tanah. Untuk mendapatkan hasil desain pondasi dangkal yang optimal, terdapat tiga kriteria penting yang harus diperhatikan yaitu Ultimate Limit State (ULS), Serviceability Limit State (SLS), dan ekonomis. Sehingga, penggunaan metode optimasi yang baik akan membantu menghasilkan dimensi pondasi yang optimal dan ekonomis namun tetap memenuhi syarat aman. Penelitian-penelitian sebelumnya mengindikasikan bahwa metode metaheuristik dapat digunakan sebagai alternatif yang mampu menyelesaikan permasalahan optimasi yang ada. Oleh karena itu, penelitian ini menggunakan metode metaheuristik Particle Swarm Optimization (PSO) dan Symbiotic Organisms Search (SOS) untuk menyelesaikan permasalahan optimasi pondasi dangkal. Pada penelitian ini, optimasi pondasi dangkal dilakukan terhadap pondasi setempat untuk studi kasus bangunan dua lantai. PSO dan SOS bekerja untuk menemukan solusi dimensi pondasi setempat yang diharapkan dapat memiliki biaya konstruksi terendah dan dibatasi oleh constraint dari SNI 8460:2017, SNI 2847:2013, dan bearing capacity theory. Hasil penelitian menunjukkan bahwa metode metaheuristik mampu menemukan dimensi pondasi dangkal yang optimal untuk masing-masing studi kasus. Selain itu, dapat dilihat apabila algoritma SOS memiliki performa yang lebih baik dari PSO.

Ultimate Limit State Based Ship Structural Design Using Multi-Objective Discrete Particle Swarm Optimization

2015 ◽  
Author(s):  
Ming Ma ◽  
Owen Hughes ◽  
Tobin McNatt
Keyword(s):  
Finite Element ◽  
Particle Swarm Optimization ◽  
Limit State ◽  
Particle Swarm ◽  
Structural Safety ◽  
Ultimate Limit State ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Ultimate Limit

Multi-objective optimization problems consist of several objectives that must be handled simultaneously. These objectives usually conflict with each other, and optimizing a particular solution with respect to a single objective can result in unacceptable results with respect to the other objectives. A reasonable solution to a multi-objective problem is to investigate a set of solutions, each of which satisfies the objectives at an acceptable level without being dominated by any other solution. Genetic or evolution algorithms have been demonstrated to be particularly effective to determine excellent solutions to these problems. Among many algorithms, the particle swarm optimization (PSO) has been found to be faster with less computational overhead. In this paper a multi-objective discrete particle swarm optimization is formulated and used to optimize a large and complex thin-wall structure on the basis of weight, safety and cost. The structure weight and cost are calculated using realistic finite element models. The design process has two stages: (1) the actual stresses are obtained by finite element analysis of the full ship, (2) for a midship segment of the ship (referred to as a “control cluster”) the structural safety is evaluated using the ALPS/ULSAP set of ultimate limit state criteria, and then the segment is optimized using any suitable optimization method (in this paper, the PSO method). Both stages involve iteration, but the process is arranged so as to keep the number of full ship finite element analyses to a minimum. The complete design process is illustrated for a 200,000 ton oil tanker. The numerical results show that the PSO method is very useful to perform ultimate strength based ship structural optimization with multi-objectives, namely minimization of the structural weight and cost and maximization of structural safety. The example also demonstrates that the proper definition of boundary conditions and design load cases is of paramount importance for design optimization.

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

2018 ◽  
Vol 19 (2) ◽  
pp. 103 ◽  
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.

scholarly journals Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm for Solving Optimal Reactive Power Dispatch Problem

2020 ◽  
Vol 3 (1) ◽  
pp. 12-21
Author(s):  
Kanagasabai Lenin
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Search Algorithm ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Symbiotic Organisms Search ◽  
Power Dispatch ◽  
Fitness Value ◽  
Symbiotic Organisms

In this work Hybridization of Genetic Particle Swarm Optimization Algorithm with Symbiotic Organisms Search Algorithm (HGPSOS) has been done for solving the power dispatch problem. Genetic particle swarm optimization problem has been hybridized with Symbiotic organisms search (SOS) algorithm to solve the problem. Genetic particle swarm optimization algorithm is formed by combining the Particle swarm optimization algorithm (PSO) with genetic algorithm (GA).  Symbiotic organisms search algorithm is based on the actions between two different organisms in the ecosystem- mutualism, commensalism and parasitism. Exploration process has been instigated capriciously and every organism specifies a solution with fitness value.  Projected HGPSOS algorithm improves the quality of the search.  Proposed HGPSOS algorithm is tested in IEEE 30, bus test system- power loss minimization, voltage deviation minimization and voltage stability enhancement has been attained.

scholarly journals Optimization of resource leveling problem under multiple objective criteria using a symbiotic organisms search

2019 ◽  
Vol 21 (1) ◽  
pp. 43-49 ◽  
Author(s):  
Doddy Prayogo ◽  
Christianto Tirta Kusuma
Keyword(s):  
Particle Swarm Optimization ◽  
Resource Management ◽  
Objective Function ◽  
Multiple Objective ◽  
Objective Functions ◽  
Swarm Optimization ◽  
Cost Overruns ◽  
Symbiotic Organisms Search ◽  
Resource Leveling ◽  
Symbiotic Organisms

Bad scheduling and resource management can cause delays or cost overruns. Optimization in solving resource leveling is necessary to avoid those problems. Several objective criteria are used to solve resource leveling. Each of them has the same objective, which is to reduce the fluctuation of resource demand of the project. This study compares the performance of particle swarm optimization (PSO) and symbiotic organisms search (SOS) in solving resource leveling problems using separate objective functions in order to find which one produces a better solution. The results show that SOS produced a better solution than PSO, and one objective function is better in solving resource leveling than the others.

End-Plate Connections in Bi-Axial Bending - Measurements

2016 ◽  
Vol 710 ◽  
pp. 275-280
Author(s):  
Jari Mäkinen ◽  
Keijo Fränti ◽  
Matti Korhonen ◽  
Joshua Fillion ◽  
Markku Heinisuo
Keyword(s):  
Bearing Capacity ◽  
Cross Section ◽  
Limit State ◽  
Ultimate Limit State ◽  
Load Bearing Capacity ◽  
End Plate ◽  
Residual Capacity ◽  
Plate Connections ◽  
Ultimate Limit ◽  
Is Strain

In this paper we consider the measurements of bolted end-plate connections of tubular beams with cold-formed hollow rectangular aluminium sections. The motivation for these measurements originates from the fact that the aluminium standard (EN 1999-1-1) [1] does not cover the design of this very frequently used type of connection, where the bolts are located outside the edge-lines of the cross-section, i.e. corner bolts. Many tests and studies regarding this area have been conducted, but this paper brings value to the case where bi-axial bending is applied. The measurements have been carried out and the detailed results shall be shown. In this paper, we will focus on the six measurements where the tubular beams were bent uniaxially and biaxially to these limit points. The tests were stopped when the ultimate limit state was reached. In this case the connection never actually broke, but effectively the joint had lost its load bearing capacity. Some residual capacity still remained, but the displacements were too great resulting in a totally different behavior of the connection. The behavior of this connection is highly non-linear, since aluminium (AW 5754) as a material is strain hardening and the mechanism in the connection changes as the displacements increase.

Design Issues about the Bar Lay-Out at the Dapped Ends of Simply-Supported One-Way R/C Slabs

2016 ◽  
Vol 711 ◽  
pp. 706-713
Author(s):  
Pietro G. Gambarova ◽  
Francesco Lo Monte
Keyword(s):  
Bearing Capacity ◽  
Limit State ◽  
Ultimate Limit State ◽  
Main Body ◽  
Concentrated Load ◽  
Bending Tests ◽  
Simply Supported ◽  
Extra Effort ◽  
Dapped Ends ◽  
Ultimate Limit

Directly-or indirectly-supported R/C slabs are frequently used in the covers of small-to-medium underground facilities, where the service loads are often rather limited, but very severe loads cannot be ruled out in accidental situations.To have fresh information on the structural performance and cracking of R/C slabs simply supported along their short sides via corbels (dapped ends), four rectangular slabs subjected to transversely distributed or concentrated loads have been recently tested in Milan (b x L = 1.30 x 2.20 m; simply-supported span = 2.10 m; thickness = 15 cm). The load was applied either at mid-span (in the bending tests, not presented in this paper), or at 1/10 of the span (in the shear tests).Two bar arrangements were investigated with straight or bent-up bars in the main body, and straight bars or hooks in the corbels.In the D zones of the slabs tested in shear, the concentrated load induces a rather complex 3-D crack pattern, with a limited reduction in the bearing capacity, compared with the cross-wise distributed load.Rather simple strut-and-tie models applied to the slabs with bent-up bars and hooks, and the equations provided by European and North-American codes for the beams devoid of transverse reinforcement are shown to yield realistic predictions for the bearing capacity at the ultimate limit state. In the former case, however, modelling the bond along the tension reinforcement of the corbel requires some care, because of bond local and global effects. Last but not least, refining bar layout confirms – once more – that slab performance can be markedly improved with little extra effort.

scholarly journals Probabilistic Approach to Limit States of a Steel Dome

Materials ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 5528
Author(s):  
Paweł Zabojszcza ◽  
Urszula Radoń ◽  
Waldemar Szaniec
Keyword(s):  
Normal Distribution ◽  
Limit State ◽  
Probabilistic Approach ◽  
Random Variables ◽  
Structural Safety ◽  
Ultimate Limit State ◽  
Limit States ◽  
Serviceability Limit State ◽  
First Case ◽  
Ultimate Limit

In this paper, Numpress Explore software, developed at the Institute of Fundamental Technological Research of the Polish Academy of Sciences (IPPT PAN), was used to conduct reliability analyses. For static-strength calculations, the MES3D module, designed by the authors, was employed. Ultimate limit state was defined as condition of non-exceedance of the capacity value, resulting from the stability criterion of the bent and compressed element. The serviceability limit state was defined as the condition of non-exceedance of allowable vertical displacement. The above conditions constitute implicit forms of random variable functions; therefore, it was necessary to build an interface between the Numpress Explore and MES3D programs. In the study, a comparative analysis of two cases was carried out. As regards the first case, all adopted random variables had a normal distribution. The second case involved a more accurate description of the quantities mentioned. A normal distribution can be adopted for the description of, e.g., the randomness in the location of the structure nodes, and also the randomness of the multiplier of permanent loads. In actual systems, the distribution of certain loads deviates substantially from the Gaussian distribution. Consequently, adopting the assumption that the loads have a normal distribution can lead to gross errors in the assessment of structural safety. The distribution of loads resulting from atmospheric conditions is decidedly non-Gaussian in character. The Gumbel distribution was used in this study to describe snow and wind loads. The modulus of elasticity and cross-sectional area were described by means of a log-normal distribution. The adopted random variables were independent. Additionally, based on an analysis of the elasticity index, the random variables most affect the failure probability in the ultimate limit state and serviceability limit state were estimated.

scholarly journals OPTIMASI TOPOLOGI DAN UKURAN PENAMPANG STRUKTUR RANGKA BATANG BAJA DENGAN METODE METAHEURISTIK

2019 ◽  
Vol 6 (1) ◽  
pp. 33-42
Author(s):  
Ricky Agusta Hartono
Keyword(s):  
Particle Swarm Optimization ◽  
Differential Evolution ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Symbiotic Organisms Search ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Symbiotic Organisms ◽  
Evolution Teaching

Optimasi topologi dari struktur rangka batang baja memberikan hasil yang lebih optimal dibandingkan optimasi ukuran penampang karena batang dan nodes yang tidak berguna pada struktur dapat dihilangkan. Fungsi objektif dari algoritma metaheuristik adalah untuk meminimalkan massa struktur rangka batang baja terhadap constraints statis dan dinamis berdasarkan studi kasus dan spesifikasi bangunan baja struktural Indonesia, SNI 1729:2015. Empat algoritma yang digunakan pada studi ini adalah: Particle Swarm Optimization, Differential Evolution, Teaching-Learning-Based Optimization, dan Symbiotic Organisms Search. Keempat algoritma tersebut diuji pada studi kasus 24-bar truss. Performa dari algoritma diukur dari lima kriteria massa, yaitu: massa terbaik, terburuk, rata-rata, standar deviasi, dan median dari struktur rangka batang baja. Hasil penelitian menunjukkan SOS menunjukkan performa terbaik pada studi kasus 24-bar truss.

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