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.

Highlights

  • Nowadays development in optimization plays a big role in civil engineering [1], especially in the design optimization of structures

  • 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

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Summary

Introduction

Nowadays development in optimization plays a big role in civil engineering [1], especially in the design optimization of structures. Many aspects and elements of a structure can be optimized to attain the best solution to the design problem. Efficiency in cost, selection of steel profiles, and even locations can be found. One of the components that can be optimized during a structural design is the steel deck floor system. As a typical section of the structure, steel deck floor system components such as beams, girders, decks as well as the slab itself, create thousands of possibilities of combinations that can suit the structure. Each steel deck floor system can be designed in a various combination that needs to be considered in the design process

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