Please use this identifier to cite or link to this item: http://hdl.handle.net/10321/3381
Title: Optimum design of steel structures using evolutionary algorithms
Authors: Dolwana, Zolisa 
Issue Date: Jan-2019
Abstract: The subject of this thesis is optimization of steel structures using evolutionary algorithms. Heuristic algorithms are used and compared for the best possible results both in two dimen-sional and three dimensional structures. The topology, shape and sizing of the optimization problem has been formulated based on practical real life problems. The design has to produce best results without violating the stress and displacement constraints. The design constraints satisfy the demands of steel material properties and the selected profiles.

Structural steel is discussed in detail on how they can be designed, and manufactured in both two dimensions (2-D) and three dimensions (3-D) to carry required loads and provide adequate rigidity. These types of structures are commonly found in the construction of build-ings, bridges, transmission line towers, industrial sheds, automotive vehicles and ships etc. Steel exhibits desirable physical properties that make it one of the most versatile structural materials in use. Its great strength, uniformity, light weight, ease of use, and many other de-sirable properties makes it the material of choice for numerous structures such as steel bridges, high rise buildings, towers, and other structures. Steel structures are formed with a specific shape following certain standards of chemical composition and strength. During the course of construction steel can be joined by welding or bolting methods.

The structural steel problem is solved using population based methods, namely, the genetic algorithm (GA), particle swarm optimization (PSO) and big bang - big crunch (BB-BC). The quality of results produced using these heuristic methods has been studied in several problems.

The present study demonstrates how progress in modern evolutionary algorithms has revolu-tionized design optimization of engineering structures. The performance of an evolutionary algorithm called the big bang - big crunch algorithm is shown by example of the steel trusses where the minimum possible weight was determined subjected to stress and displacement constraints.
Description: Submitted in fulfillment of the academic requirements for the degree of Master of Engineering in Mechanical Engineering, Durban University of Technology, Durban, South Africa. 2019.
URI: http://hdl.handle.net/10321/3381
Appears in Collections:Theses and dissertations (Engineering and Built Environment)

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