Multi-objective optimal design of steel MRF buildings based on life-cycle cost using a swift algorithm

Structures ◽  
2021 ◽  
Vol 34 ◽  
pp. 4041-4059
Author(s):  
Ali Ghasemof ◽  
Masoud Mirtaheri ◽  
Reza Karami Mohammadi ◽  
Mohammad Reza Mashayekhi
2011 ◽  
Vol 121-126 ◽  
pp. 2223-2227 ◽  
Author(s):  
Chun Sheng Zhu ◽  
Qi Zhang ◽  
Fan Tun Su ◽  
Hong Liang Ran

By weighing reliability, maintainability, availability and life-cycle cost of equipment which are influenced by testability,the testability indexes of system level BIT are determined on the basis of maximum system reliability & maintainability and minimum the life-circle cost. The influence mathematical models of system reliability, maintainability, availability and life-circle cost are established. According to these mathematical models, the multi-objective optimization model of system-level BIT testability indexes is established. The multi-objective optimization model is solved using Non-dominated Sorting Genetic Algorithm II, and the validity of the multi-objective optimization model is proved through an example.


Author(s):  
Baran Yeter ◽  
Yordan Garbatov ◽  
Carlos Guedes Soares

The present work carries out a multi-objective design optimization of a monopile offshore wind turbine support structure. Three objective functions are created related to the minimization of the total construction cost of the monopile support structure, fatigue damage, and permissible stress ratio. The construction cost takes into account the costs associated with welding and labor. The constructional limitations in the offshore industry take into consideration in the selection of the upper boundaries of the design variables. The reliability index is employed to identify the topology of the structure as a part of the Pareto frontier solution in reducing the failure probability for the critical limit states and satisfying the target reliability level. A risk-based assessment of the optimal designs is performed and the output is used to update the life-cycle cost assessment. The ultimate optimization target is deemed to be the minimization of the levelised cost of energy, which is estimated based on the discounted cash-flow method considering the life-cycle costs constituting CAPEX and OPEX.


Author(s):  
Swati Sirsant ◽  
M. Janga Reddy

Abstract Designing the Water Distribution Networks (WDNs) consists of finding out pipe sizes such that the demands are satisfied and the desired performance levels are achieved at minimum cost. However, WDNs are subject to many future changes such as an increase (or decrease) in demand due to population change and migration, changes in water availability due to seasonal and climatic change, etc. Thus, the capacity expansion of WDNs needs to be performed such that the cost of interventions made is minimum while satisfying the demand and performance requirements at various time periods. Therefore, the current study proposed a Dynamic Programming (DP) framework for capacity expansion of WDNs and solved using Multi-Objective Self Adaptive Differential Evolution (MOSADE). The methodology is tested on three benchmark WDNs, namely Two-loop (TL), GoYang, and Blacksburg (BLA) WDNs, and applied to a real case study of the Badlapur region Maharashtra, India. The results show that the proposed methodology leads to effective Pareto optimal fronts, making it an efficient method for solving WDN expansion problems. Subsequently, an Analytical Hierarchy Process (AHP) based multi-criteria decision-making (MCDM) analysis was performed on the obtained Pareto-optimal solutions to determine the most suitable solution based on three criteria: Life Cycle Cost (LCC) of expansions, hydraulic reliability, and mechanical reliability. The main advantage of the proposed methodology is its capability to consider hydraulic performance as well as structural integrity and demand satisfaction in the face of hydraulic and mechanical failures.


2018 ◽  
Vol 21 (15) ◽  
pp. 2227-2240 ◽  
Author(s):  
Yu-Jing Li ◽  
Hong-Nan Li

Considering future seismic risk and life-cycle cost, the life-cycle seismic design of bridge is formulated as a preference-based multi-objective optimization and decision-making problem, in which the conflicting design criteria that minimize life-cycle cost and maximize seismic capacity are treated simultaneously. Specifically, the preference information based on theoretical analysis and engineering judgment is embedded in the optimization procedure. Based on reasonable displacement ductility, the cost preference and safety preference information are used to progressively construct value function, directing the evolutionary multi-objective optimization algorithm’s search to more preferred solutions. The seismic design of a reinforced concrete pier is presented as an application example using the proposed procedure for the global Pareto front corresponding with engineering designers’ preference. The results indicate that the proposed model is available to find the global Pareto front satisfying the corresponding preference and overcoming the difficulties of the traditional multi-objective optimization algorithm in obtaining a full approximation of the entire Pareto optimal front for large-dimensional problems as well as cognitive difficulty in selecting one preferred solution from all these solutions.


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