A GENETIC ALGORITHM–BASED APPROACH TO PREDICT PAVEMENT MAINTENANCE STRATEGIES: IRAQI EXPRESSWAY NO.1 CASE STUDY

2016 ◽  
Author(s):  
Namir G. Ahmed Alkawaaz
Keyword(s):  
Genetic Algorithm ◽  
Maintenance Strategies ◽  
Pavement Maintenance

scholarly journals AN INTEGRATED MULTI-OBJECTIVES OPTIMIZATION APPROACH ON MODELLING PAVEMENT MAINTENANCE STRATEGIES FOR PAVEMENT SUSTAINABILITY

2020 ◽  
Vol 26 (8) ◽  
pp. 717-732
Author(s):  
Ankang Ji ◽  
Xiaolong Xue ◽  
Yuna Wang ◽  
Xiaowei Luo ◽  
Minggong Zhang
Keyword(s):  
Integrated Approach ◽  
Maintenance Cost ◽  
First Year ◽  
Optimization Approach ◽  
Maintenance Strategies ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Road Pavement ◽  
Maintenance Activities

Addressing the multi-dimensional challenges to promote pavement sustainability requires the development of an optimization approach by simultaneously taking into account future pavement conditions for pavement maintenance with the capability to search and determine optimal pavement maintenance strategies. Thus, this research presents an integrated approach based on the Markov chain and Particle swarm optimization algorithm which aims to consider the predicted pavement condition and optimize the pavement maintenance strategies during operation when applied in the maintenance management of a road pavement section. A case study is conducted for testing the capability of the proposed integrated approach based on two maintenance perspectives. For case 1, maintenance activities mainly occur in TM20, TM31, and TM41, with the maximum maintenance mileage reaching 88.49 miles, 50.89 miles, and 20.91 miles, respectively. For case 2, the largest annual maintenance cost in the first year is $15.16 million with four types of maintenance activities. Thereafter, the maintenance activities are performed at TM10, TM31, and TM41, respectively. The results obtained, compared with the linear program, show the integrated approach is effective and reliable for determining the maintenance strategy that can be employed to promote pavement sustainability.

Multi-objective optimization of safety instrumented systems maintenance strategy: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Hafed Touahar ◽  
Nouara Ouazraoui ◽  
Nor El Houda Khanfri ◽  
Mourad Korichi ◽  
Bilal Bachi ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Life Cycle ◽  
Environmental Risks ◽  
Life Cycle Costs ◽  
Maintenance Strategy ◽  
Maintenance Strategies ◽  
Content Type ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

PurposeThe main objective of safety instrumented systems (SISs) is to maintain a safe condition of a facility if hazardous events occur. However, in some cases, SIS's can be activated prematurely, these activations are characterized in terms of frequency by a Spurious Trip Rate (STR) and their occurrence leads to significant technical, economic and even environmental losses. This work aims to propose an approach to optimize the performances of the SIS by a multi-objective genetic algorithm. The optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).Design/methodology/approachThe optimization of SIS performances is performed using the multi-objective genetic algorithm by minimizing their probability of failure on demand PFDavg, Spurious Trip Rate (STR) and Life Cycle Costs (LCCavg). A set of constraints related to maintenance costs have been established. These constraints imply specific maintenance strategies which improve the SIS performances and minimize the technical, economic and environmental risks related to spurious shutdowns. Validation of such an approach is applied to an Emergency Shutdown (ESD) of the blower section of an industrial facility (RGTE- In Amenas).FindingsA case study concerning a safety instrumented system implemented in the RGTE facility has shown the great applicability of the proposed approach and the results are encouraging. The results show that the selection of a good maintenance strategy allows a very significant minimization of the PFDavg, the frequency of spurious trips and Life Cycle Costs of SIS.Originality/valueThe maintenance strategy defined by the system designer can be modified and improved during the operational phase, in particular safety systems. It constitutes one of the least expensive investment strategies for improving SIS performances. It has allowed a considerable minimization of the SIS life cycle costs; PFDavg and the frequency of spurious trips.

Establishing optimal project-level strategies for pavement maintenance and rehabilitation – A framework and case study

2012 ◽  
Vol 44 (5) ◽  
pp. 565-589 ◽  
Author(s):  
Muhammad Irfan ◽  
Muhammad Bilal Khurshid ◽  
Qiang Bai ◽  
Samuel Labi ◽  
Thomas L. Morin
Keyword(s):  
Pavement Maintenance ◽  
Maintenance And Rehabilitation ◽  
Project Level

scholarly journals Hybrid Seven-bar Press Mechanism

2018 ◽  
Vol 12 (3) ◽  
pp. 181-187
Author(s):  
M. Erkan Kütük ◽  
L. Canan Dülger
Keyword(s):  
Genetic Algorithm ◽  
Objective Function ◽  
Design Optimization ◽  
Hybrid System ◽  
Degrees Of Freedom ◽  
Dimensional Synthesis ◽  
Design Variables ◽  
Optimization Study ◽  
Metal Stamping

An optimization study with kinetostatic analysis is performed on hybrid seven-bar press mechanism. This study is based on previous studies performed on planar hybrid seven-bar linkage. Dimensional synthesis is performed, and optimum link lengths for the mechanism are found. Optimization study is performed by using genetic algorithm (GA). Genetic Algorithm Toolbox is used with Optimization Toolbox in MATLAB®. The design variables and the constraints are used during design optimization. The objective function is determined and eight precision points are used. A seven-bar linkage system with two degrees of freedom is chosen as an example. Metal stamping operation with a dwell is taken as the case study. Having completed optimization, the kinetostatic analysis is performed. All forces on the links and the crank torques are calculated on the hybrid system with the optimized link lengths

scholarly journals Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Electricity ◽  
2021 ◽  
Vol 2 (1) ◽  
pp. 91-109
Author(s):  
Julian Wruk ◽  
Kevin Cibis ◽  
Matthias Resch ◽  
Hanne Sæle ◽  
Markus Zdrallek
Keyword(s):  
Genetic Algorithm ◽  
Electric Vehicle ◽  
Electric Vehicles ◽  
Low Voltage ◽  
Network Planning ◽  
Voltage Regulation ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
The Impact

This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.

Design and Evaluation of Usable Systems

2002 ◽  
Vol 46 (3) ◽  
pp. 367-371
Author(s):  
John F. McGrew
Keyword(s):  
Genetic Algorithm ◽  
Change Management ◽  
Management System ◽  
Design Method ◽  
The Other ◽  
Design Team ◽  
Style Analysis ◽  
Decision Style ◽  
Parallel Design

This paper discusses a case study of a design and evaluation of a change management system at a large Telecommunications Corporation. The design and evaluation were done using the facilitated genetic algorithm (a parallel design method) and user decision style analysis. During the facilitated genetic algorithm the design team followed the procedure of the genetic algorithm. Usability was evaluated by applying user decision style analysis to the designed system. The design is compared with an existing system and with one designed by an analyst. The change management system designed by the facilitated genetic algorithm took less time to design and decision style analysis indicated it would be easier to use than the other two systems.

An Improved Ant Colony Optimization Algorithm for Solving the TSP Problem

2010 ◽  
Vol 26-28 ◽  
pp. 620-624 ◽  
Author(s):  
Zhan Wei Du ◽  
Yong Jian Yang ◽  
Yong Xiong Sun ◽  
Chi Jun Zhang ◽  
Tuan Liang Li
Keyword(s):  
Genetic Algorithm ◽  
Ant Colony Algorithm ◽  
Ant Colony ◽  
Convergence Time ◽  
Ant Colony Optimization Algorithm ◽  
Data Set ◽  
Research Attention ◽  
Simply Supported ◽  
Source Data

This paper presents a modified Ant Colony Algorithm(ACA) called route-update ant colony algorithm(RUACA). The research attention is focused on improving the computational efficiency in the TSP problem. A new impact factor is introduced and proved to be effective for reducing the convergence time in the RUACA performance. In order to assess the RUACA performance, a simply supported data set of cities, which was taken as the source data in previous research using traditional ACA and genetic algorithm(GA), is chosen as a benchmark case study. Comparing with the ACA and GA results, it is shown that the presented RUACA has successfully solved the TSP problem. The results of the proposed algorithm are found to be satisfactory.

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