Electronic Theses and Dissertations

Date

2022

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Civil Engineering

Committee Chair

Charles Camp

Committee Member

Shahram Pezeshk

Committee Member

Roger Meier

Committee Member

Mihalis Golias

Abstract

The main application of optimization algorithms to engineering problems is to facilitate the problem-solving procedure by finding good solutions. In this way, there are two main categories of problems that are tackled by the optimization algorithms: analyzing and designing. The key part of an optimization project, in addition to the type of algorithms, is objective functions. Therefore, a good understanding of the nature of the problems at hand would be crucial for defining the optimization procedure. To be more precise, it is important how to define the bboundaries of the input parameters, the applied constraints and estimate the objective values. This dissertation is aimed to implement recent optimization algorithms for finding cost-effective designs for different structures. The underlying goal is to automate the cost-effective design procedure, find efficient optimizers, explore the interactions of conflicting objectives through multi-objective optimization and see their effects on the final results. In this way, different MATLAB codes are developed to automate the design procedures of reinforced concrete cantilever retaining walls (RCC wall), mechanically stabilized earth retaining walls (MSE wall), shallow foundations, and combined footing. Moreover, the performance of a wide range of swarm-intelligence-based and evolutionary algorithms are explored in solving the mentioned problems. A self-adaptive hybrid evolutionary optimization algorithm is developed based on combining genetic algorithm (GA) and particle swarm optimization (PSO) called GAPSO to enhance the performance of recent variants of GA and PSO as much as possible. This algorithm is applied to the problem of RCC wall optimization. Cost minimization and factor of safety (FOS) maximization as two conflicting objectives for retaining structures optimization problems are studied in a multi-objective optimization process. In this way, FOSs of the wall against overturning, sliding, and bearing capacity are summed up and are considered as a single objective. In all the design procedures, the requirements for structural strength and geotechnical stability are checked to guarantee the serviceability of the proposed designs.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.

Notes

Open Access

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