Optimasi Ukuran Penampang Rangka Batang Baja berdasarkan SNI 1729:2015 dengan Metode Metaheuristik Symbiotic Organisms Search

https://doi.org/10.5614/jts.2018.25.1.6

Authors

  • Doddy Prayogo Petra Christian University
  • Wong Foek Tjong Program Studi Magister Teknik Sipil, Universitas Kristen Petra
  • Ricky Gunawan Program Studi Teknik Sipil, Universitas Kristen Petra
  • Stefano Kusuma Ali Program Studi Teknik Sipil, Universitas Kristen Petra
  • Steven Sugianto Program Studi Magister Teknik Sipil, Universitas Kristen Petra

Keywords:

Rangka batang, optimasi, metaheuristik, SNI 1729, 2015, symbiotic organisms search

Abstract

Abstrak

Penelitian ini menyelidiki metode metaheuristik baru bernama symbiotic organisms search (SOS) dalam mengoptimasi ukuran penampang rangka batang baja. Syarat batasan desain diadopsi dari spesifikasi untuk bangunan gedung baja struktural, SNI 1729:2015, yaitu rasio gaya terhadap kapasitas dan rasio kelangsingan batang. Lima studi kasus optimasi struktur rangka batang digunakan untuk menguji performa dari SOS. Hasil simulasi dengan metode SOS ini kemudian akan dibandingkan terhadap tiga metode metaheuristik lainnya, yaitu particle swarm optimization, differential evolution, dan teaching"“learning-based optimization. Hasil penelitian menunjukkan bahwa algoritma SOS lebih superior dan mempunyai kemampuan konvergensi yang lebih baik dibandingkan dengan metode metaheuristik lainnya dalam menyelesaikan problem optimasi struktur rangka batang.

Abstract

This study investigates a new metaheuristic method called symbiotic organisms search (SOS) for sizing optimization of steel truss structures. The design constraints are adopted from SNI 1729:2015 Indonesian code specification for structural steel buildings that includes the constraints on slenderness ratio and force capacity. Five practical case studies of truss design are employed to test the performance of the SOS algorithm. The simulation results of the SOS are compared to other metaheuristic methods, namely, the particle swarm optimization, differential evolution, and teaching learning-based optimization, in terms of accuracy and consistency. The results show the superiority of the SOS as well as excellent convergence behavior over the other metaheuristic algorithms in solving the truss structure optimization problems.

 

References

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Published

2018-04-06

Issue

Section

Articles