A stakeholder probability-based optimization approach for cost-effective bridge management under financial constraints

2011 ◽  
Vol 33 (5) ◽  
pp. 1439-1449 ◽  
Author(s):  
André D. Orcesi ◽  
Dan M. Frangopol
Keyword(s):  
Financial Constraints ◽  
Cost Effective ◽  
Optimization Approach ◽  
Bridge Management

scholarly journals Toward Decentralised Sanitary Sewage Collection Systems: A Multiobjective Approach for Cost-Effective and Resilient Designs

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1886
Author(s):  
Arezoo Zahediasl ◽  
Amin E. Bakhshipour ◽  
Ulrich Dittmer ◽  
Ali Haghighi
Keyword(s):  
Treatment Plant ◽  
Drainage System ◽  
Cost Effective ◽  
Optimization Approach ◽  
Hydraulic Design ◽  
Multiobjective Approach ◽  
Layout Generation ◽  
Plant Allocation ◽  
Problem Solving Process

In recent years, the concept of a centralized drainage system that connect an entire city to one single treatment plant is increasingly being questioned in terms of the costs, reliability, and environmental impacts. This study introduces an optimization approach based on decentralization in order to develop a cost-effective and sustainable sewage collection system. For this purpose, a new algorithm based on the growing spanning tree algorithm is developed for decentralized layout generation and treatment plant allocation. The trade-off between construction and operation costs, resilience, and the degree of centralization is a multiobjective problem that consists of two subproblems: the layout of the networks and the hydraulic design. The innovative characteristics of the proposed framework are that layout and hydraulic designs are solved simultaneously, three objectives are optimized together, and the entire problem solving process is self-adaptive. The model is then applied to a real case study. The results show that finding an optimum degree of centralization could reduce not only the network’s costs by 17.3%, but could also increase its structural resilience significantly compared to fully centralized networks.

scholarly journals A delayed differentiation multiproduct model with the outsourcing of common parts, overtime strategy for end products, and quality reassurance

2021 ◽  
pp. 143-158 ◽  
Author(s):  
Singa Wang Chiu ◽  
Victoria Chiu ◽  
Ming-Hon Hwang ◽  
Yuan-Shyi Peter Chiu
Keyword(s):  
Cost Effective ◽  
Sensitivity Analyses ◽  
Optimization Approach ◽  
Limited Capacity ◽  
Numerical Illustration ◽  
Delayed Differentiation ◽  
Modeling Analysis ◽  
End Products ◽  
Effective Decision ◽  
Effective Decision Making

Production planners today must simultaneously face with the time and quality demands of various goods externally and meet limited capacity internally. This study presents a two-stage delayed- differentiation multiproduct model that considers the outsourcing options for common parts, overtime strategy for end products, and quality reassurance to assist in making fabrication runtime decisions that are cost-effective. Stage one produces all necessary common intermediate components for end products. To reduce stage one’s utilization/uptime, this study adopts a partial outsourcing option. Stage two uses an overtime strategy to fabricate end products that further shorten the uptime. The production processes in both phases are assumed to be imperfect. This study employs the reworking/scrapping of random faulty items to reassure product quality. The researchers build a model to depict the proposed problem’s characteristics and used the mathematical modeling, analysis, and optimization approach to determine the best rotation cycle length that minimizes the system’s expenses. Further, in this study, the researchers provide sensitivity analyses and a numerical illustration, which validate the result’s applicability and exhibit its capability. This result contributes to practical multiproduct-fabrication by (1) deriving the optimal manufacturing policy for a delayed-differentiation multiproduct system with dual uptime reduction policies and quality reassurance; and (2) offering a decisional model that allows production planners to explore the collective/separate effect of a quality-ensured and dual uptime reduction strategy on a problem’s operating policy and crucial system performance indicators, which assists in cost-effective decision-making.

Design and Analysis of Automotive Bumper Covers in Transient Loading Conditions

2016 ◽  
Vol 715 ◽  
pp. 174-179 ◽  
Author(s):  
Chih Hsing Liu ◽  
Ying Chia Huang ◽  
Chen Hua Chiu ◽  
Yu Cheng Lai ◽  
Tzu Yang Pai
Keyword(s):  
Optimal Design ◽  
Numerical Model ◽  
Design Method ◽  
Experimental Tests ◽  
Cost Effective ◽  
Limited Range ◽  
Optimization Approach ◽  
Loading Conditions ◽  
Element Analysis ◽  
Design Guideline

This paper presents the analysis methods for design of automotive bumper covers. The bumper covers are plastic structures attached to the front and rear ends of an automobile and are expected to absorb energy in a minor collision. One requirement in design of the bumper covers is to minimize the bumper deflection within a limited range under specific loadings at specific locations based on the design guideline. To investigate the stiffness performance under various loading conditions, a numerical model based on the explicit dynamic finite element analysis (FEA) using the commercial FEA solver, LS-DYNA, is developed to analyze the design. The experimental tests are also carried out to verify the numerical model. The thickness of the bumper cover is a design variable which usually varies from 3 to 4 mm depending on locations. To improve the stiffness of the bumper, an optimal design for the bumper under a pre-defined loading condition is identified by using the topology optimization approach, which is an optimal design method to obtain the optimal layout of an initial design domain under specific boundary conditions. The outcome of this study provides an efficient and cost-effective method to predict and improve the design of automotive bumper covers.

scholarly journals Unsupervised Parameterization for Optimal Segmentation of Agricultural Parcels from Satellite Images in Different Agricultural Landscapes

2020 ◽  
Vol 12 (18) ◽  
pp. 3096
Author(s):  
Gideon Okpoti Tetteh ◽  
Alexander Gocht ◽  
Marcel Schwieder ◽  
Stefan Erasmi ◽  
Christopher Conrad
Keyword(s):  
Evaluation System ◽  
Reference Data ◽  
Cost Effective ◽  
Agricultural Landscapes ◽  
Bayesian Optimization ◽  
Absolute Difference ◽  
Optimization Approach ◽  
Lower Saxony ◽  
Optimal Segmentation ◽  
Unsupervised Methods

Image segmentation is a cost-effective way to obtain information about the sizes and structural composition of agricultural parcels in an area. To accurately obtain such information, the parameters of the segmentation algorithm ought to be optimized using supervised or unsupervised methods. The difficulty in obtaining reference data makes unsupervised methods indispensable. In this study, we evaluated an existing unsupervised evaluation metric that minimizes a global score (GS), which is computed by summing up the intra-segment uniformity and inter-segment dissimilarity within a segmentation output. We modified this metric and proposed a new metric that uses absolute difference to compute the GS. We compared this proposed metric with the existing metric in two optimization approaches based on the Multiresolution Segmentation (MRS) algorithm to optimally delineate agricultural parcels from Sentinel-2 images in Lower Saxony, Germany. The first approach searches for optimal scale while keeping shape and compactness constant, while the second approach uses Bayesian optimization to optimize the three main parameters of the MRS algorithm. Based on a reference data of agricultural parcels, the optimal segmentation result of each optimization approach was evaluated by calculating the quality rate, over-segmentation, and under-segmentation. For both approaches, our proposed metric outperformed the existing metric in different agricultural landscapes. The proposed metric identified optimal segmentations that were less under-segmented compared to the existing metric. A comparison of the optimal segmentation results obtained in this study to existing benchmark results generated via supervised optimization showed that the unsupervised Bayesian optimization approach based on our proposed metric can potentially be used as an alternative to supervised optimization, particularly in geographic regions where reference data is unavailable or an automated evaluation system is sought.

scholarly journals Bridge Management Strategy Based on Extreme User Costs for Bridge Network Condition

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Ladislaus Lwambuka ◽  
Primus V. Mtenga
Keyword(s):  
Multiobjective Optimization ◽  
Traffic Flow ◽  
Developed Countries ◽  
Optimization Approach ◽  
User Cost ◽  
Bridge Management ◽  
User Costs ◽  
First Case ◽  
Conflicting Objectives ◽  
Alternative Routes

This paper presents a practical approach for prioritization of bridge maintenance within a given bridge network. The maintenance prioritization is formulated as a multiobjective optimization problem where the simultaneous satisfaction of several conflicting objectives includes minimization of maintenance costs, maximization of bridge deck condition, and minimization of traffic disruption and associated user costs. The prevalence of user cost during maintenance period is twofold; the first case refers to the period of dry season where normally the traffic flow is diverted to alternative routes usually resurfaced to regain traffic access. The second prevalence refers to the absence of alternative routes which is often the case in the least developed countries; in this case the user cost referred to results from the waiting time while the traffic flow is put on hold awaiting accomplishment of the maintenance activity. This paper deals with the second scenario of traffic closure in the absence of alternative diversion routes which in essence results in extreme user cost. The paper shows that the multiobjective optimization approach remains valid for extreme cases of user costs in the absence of detour roads as often is the scenario in countries with extreme poor road infrastructure.

Simultaneous Determination of Disassembly Sequence and Disassembly-to-Order Decisions Using Simulation Optimization

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Mehmet Ali Ilgin ◽  
Gökçeçiçek Tuna Taşoğlu
Keyword(s):  
Simultaneous Determination ◽  
Simulation Optimization ◽  
Public Awareness ◽  
Cost Effective ◽  
Product Recovery ◽  
Optimization Approach ◽  
Order Problem ◽  
Disassembly Sequence ◽  
Disassembly Sequencing

Strict environmental regulations and increasing public awareness toward environmental issues force many companies to establish dedicated facilities for product recovery. All product recovery options require some level of disassembly. That is why, the cost-effective management of product recovery operations highly depends on the effective planning of disassembly operations. There are two crucial issues common to most disassembly systems. The first issue is disassembly sequencing which involves the determination of an optimal or near optimal disassembly sequence. The second issue is disassembly-to-order (DTO) problem which involves the determination of the number of end of life (EOL) products to process to fulfill the demand for specified numbers of components and materials. Although disassembly sequencing decisions directly affects the various costs associated with a disassembly-to-order problem, these two issues are treated separately in the literature. In this study, a genetic algorithm (GA) based simulation optimization approach was proposed for the simultaneous determination of disassembly sequence and disassembly-to-order decisions. The applicability of the proposed approach was illustrated by providing a numerical example and the best values of GA parameters were identified by carrying out a Taguchi experimental design.

scholarly journals Technological developments as an answer to bridge management challenges

2019 ◽  
Author(s):  
Andre Orcesi ◽  
Bruno Godart ◽  
Laurent Gaillet ◽  
Franziska Schmidt ◽  
Nicolas Bardou ◽  
...  
Keyword(s):  
Cost Effective ◽  
Bridge Management ◽  
Monitoring Methods ◽  
High Expectations ◽  
Bridge Monitoring ◽  
Technological Developments ◽  
Integrated Cost ◽  
And Performance ◽  
And Shifts ◽  
Non Destructive

<p>Bridge management is a challenge as owners have to deal with limited financial resources to maintain the functionalities and safety of ageing structures. Demands on transportation networks change, due to regulatory developments, society's evolution and shifts with high expectations on the operational performance of roadway bridges with reduced congestion, delay, and accidents. To minimize intrusion in the transport flow, inspection and monitoring methods should be non-destructive, minimally invasive. They should be capable of yielding rapid and accurate inspection results allowing an adequate response from the asset manager. Research aims at including autonomously operating equipment (e.g. robotics), non-intrusive (remote or proximity) observation techniques, or other methods that ensure quality and performance control of the roadway bridges in time, more safely, more quickly and/or to a higher degree of accuracy and precision.The innovation subgroup in COST action TU1406 investigates novel condition monitoring and sensing technologies for the assessment of structural serviceability and safety. Advanced, integrated, cost-effective and reliable instrumentation solutions, techniques and concepts are looked at with the aim to provide data, that will be used to compute innovative performance indicators. In this context, this paper briefly reminds some significant challenges associated with bridge management and presents three examples of innovation in bridge monitoring and NDT investigation techniques.</p>

Systematic Procedures for the Analysis of Agency and User Costs of Bridge Repair Actions

2018 ◽  
Vol 2672 (12) ◽  
pp. 116-126
Author(s):  
Ehsan Fereshtehnejad ◽  
Jieun Hur ◽  
Abdollah Shafieezadeh ◽  
Mike Brokaw ◽  
Brad Noll ◽  
...  
Keyword(s):  
Cost Estimation ◽  
Cost Effective ◽  
Agency Cost ◽  
User Cost ◽  
Bridge Management ◽  
User Costs ◽  
Vehicle Operation ◽  
Traffic Delays ◽  
Implementation Costs ◽  
The Cost

A primary goal of bridge management systems is to identify maintenance, repair, and replacement (MR&R) strategies that maximize benefits and minimize losses, often expressed in terms of cost. A major factor that greatly impacts outcomes of these frameworks, that is, the most appropriate MR&R strategies, is the cost of implementation and associated consequences of performing such actions. Given that the inventory of bridges maintained by a state department of transportation (DOT) is significantly large, this study is aimed at developing a systematic procedure to reliably estimate the costs through effective utilization of DOTs’ databases. The considered costs include agency cost of administration, engineering, and mobilization; agency direct cost of performing MR&R actions; agency cost of maintenance of traffic; and user cost incurred from traffic delays, vehicle operation, and excess emissions. The study develops a set of models to estimate the duration of various MR&R work plans. These models are subsequently used to propose analytical formulations and algorithms for the estimation of the above costs. The proposed procedures are employed to estimate the agency and user costs associated with a series of light to extensive repair actions for three bridges in Ohio. Independent calculation of some of these costs by Ohio DOT engineers indicated good agreement with results obtained from the proposed systematic methods. The verified procedures for cost estimation developed in this study enable state DOTs and other entities to reliably estimate implementation costs of actions for their large inventory of bridges and identify the most cost-effective MR&R strategies and work plans.

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