Download or read book Optimization in Pavement Management at Network Level Using Evolutionary Algorithms written by Choon Yong Tan and published by . This book was released on 1995 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multi objective optimization in pavement management using genetic algorithms and efficient surfaces written by Charles Conway Pilson and published by . This book was released on 1999 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evolutionary Data Clustering Algorithms and Applications written by Ibrahim Aljarah and published by Springer Nature. This book was released on 2021-02-20 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth analysis of the current evolutionary clustering techniques. It discusses the most highly regarded methods for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms. In addition, the book provides a comprehensive review of the fitness functions and evaluation measures that are used in most of evolutionary clustering algorithms. Furthermore, it provides a conceptual analysis including definition, validation and quality measures, applications, and implementations for data clustering using classical and modern nature-inspired techniques. It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization. The book also covers applications of evolutionary data clustering in diverse fields such as image segmentation, medical applications, and pavement infrastructure asset management.

Download or read book Comprehensively Optimized Pavement Management System for Low volume Paved Roads written by Marwan Hafez and published by . This book was released on 2019 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: State Departments of Transportation (DOTs) are trying to utilize the best practices of managing low-volume roads (LVRs) due to limited resources and declined transportation funding. Diverse maintenance practices and fluctuating budget allocations are noticed on LVRs which significantly impact the overall pavement performance. In this study, the optimal scheduling of maintenance strategies and effectiveness of treatment options are investigated. Pavement maintenance decision making is supported by three approaches: subjective judgment of pavement engineers; historical data on past practice (i.e., historical pavement performance plots); and optimization-based procedures. The three approaches are integrated using a pavement management data of Colorado LVRs to provide guidelines and recommendations for Colorado DOT (CDOT) and other transportation agencies. The accumulated field experience of Colorado DOT’s pavement engineers is highlighted through a regional survey of practice. In addition, the effectiveness of low-cost treatments on the individual pavement distresses is evaluated using historical values of pavement condition indices. It was concluded that some surface treatments and recycling techniques are effective long-term treatments for fatigue, longitudinal, and transverse cracking. However, the effectiveness of these treatments depends mainly on the initial condition index. Then, an optimization analysis is conducted using genetic algorithms to provide cost-effective capital improvement plans statewide and for deteriorated LVRs with marginal pavement conditions. The large-scale optimization analysis is limited on LVRs for statewide maintenance planning. In this study, the developed optimization models have the ability to maximize the overall pavement condition of LVRs network considering an annual budget constraint. They can also minimize the maintenance costs to achieve desired performance targets by the end of the analysis period. It was concluded that most CDOT engineering regions do not have sufficient maintenance budgets to sustain the network-level pavement condition of LVRs. The results from optimization analysis provide more realistic solutions to define the budget needs on LVRs. Moreover, an effective decision-making process is achieved for each Colorado DOT’s engineering region using a machine-learning approach. Multiple treatment alternatives are proposed using artificial neural networks with pattern recognition algorithms. It was found that these approaches provide beneficial guidelines for managing LVRs in Colorado and nationwide. As a result of this study, transportation agencies can determine future budget needs, funding allocations, and treatment policies in order to demonstrate the best possible use of pavement management resources on LVRs.

Download or read book Optimization Modeling for an Enhanced Network level Pavement Management System written by J. R. Mbwana and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Development and Implementation of a Network level Pavement Optimization Model written by Shuo Wang and published by . This book was released on 2011 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal use of pavement maintenance and rehabilitation dollars is essential in a constrained budget environment such as now. A network-level optimization tool, which could generate the best maintenance and rehabilitation strategies for the entire pavement network, has become necessary for many highway agencies. This thesis presents the development and implementation of a network-level optimization tool within a pavement management information system for the Ohio Department of Transportation (ODOT). Future pavement condition is predicted based on historical pavement data using a Markov transition probability model. Such transition probabilities are updated automatically when new condition data become available each year. The network-level optimization tool integrates a linear programming model and the Markov transition probability model. This optimization tool is capable of (1) calculating the minimum budget required to achieve a desired level of pavement network condition, (2) maximizing the improvements of pavement network condition with a given amount of budget, and (3) determining the corresponding optimal treatment policy and budget allocations. It can be used by highway agencies as a decision support tool for network-level pavement management.

Download or read book Network Level Priority Planning Optimization Models for Local Pavement Management written by Florence B. Ni and published by . This book was released on 1994 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multi objective Optimization for Bridge Management Systems written by National Cooperative Highway Research Program and published by Transportation Research Board. This book was released on 2007 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accompanying CD-ROM contains ... "[u]sers manual and software for NCHRP Report 590: Multi-objective optimization for bridge management systems."--CD-ROM label.

Download or read book Joint Optimization of Pavement Management and Reconstruction Policies for Segment and System Problems written by Jinwoo Lee and published by . This book was released on 2015 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation presents a methodology for the joint optimization of a variety of pavement construction and management activities for segment and system problems under multiple budget constraints. The objective of pavement management is to minimize the total discounted life time costs for the agency and the highway users by finding optimal policies. The scope of the dissertation is focused on continuous time and continuous state formulations of pavement condition. We use a history-dependent pavement deterioration model to account for the influence of history on the deterioration rate. Three topics, representing different aspects of the problem are covered in the dissertation. In the first part, the subject is the joint optimization of pavement design, maintenance and rehabilitation (M & R) strategies for the segment-level problem. A combination of analytical and numerical tools is proposed to solve the problem. In the second part of the dissertation, we present a methodology for the joint optimization of pavement maintenance, rehabilitation and reconstruction (MR & R) activities for the segment-level problem. The majority of existing Pavement Management Systems (PMS) do not optimize reconstruction jointly with maintenance and rehabilitation policies. We show that not accounting for reconstruction in maintenance and rehabilitation planning results in suboptimal policies for pavements undergoing cumulative damage in the underlying layers (base, sub-base or subgrade). We propose dynamic programming solutions using an augmented state which includes current surface condition and age. In the third part, we propose a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. Within a bottom-up solution approach, Genetic Algorithm (GA) is adopted. The complexity of the algorithm is polynomial in the size of the system and the policy-related parameters.

Download or read book Computational Intelligence Optimization and Inverse Problems with Applications in Engineering written by Gustavo Mendes Platt and published by Springer. This book was released on 2018-09-25 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on metaheuristic methods and its applications to real-world problems in Engineering. The first part describes some key metaheuristic methods, such as Bat Algorithms, Particle Swarm Optimization, Differential Evolution, and Particle Collision Algorithms. Improved versions of these methods and strategies for parameter tuning are also presented, both of which are essential for the practical use of these important computational tools. The second part then applies metaheuristics to problems, mainly in Civil, Mechanical, Chemical, Electrical, and Nuclear Engineering. Other methods, such as the Flower Pollination Algorithm, Symbiotic Organisms Search, Cross-Entropy Algorithm, Artificial Bee Colonies, Population-Based Incremental Learning, Cuckoo Search, and Genetic Algorithms, are also presented. The book is rounded out by recently developed strategies, or hybrid improved versions of existing methods, such as the Lightning Optimization Algorithm, Differential Evolution with Particle Collisions, and Ant Colony Optimization with Dispersion – state-of-the-art approaches for the application of computational intelligence to engineering problems. The wide variety of methods and applications, as well as the original results to problems of practical engineering interest, represent the primary differentiation and distinctive quality of this book. Furthermore, it gathers contributions by authors from four countries – some of which are the original proponents of the methods presented – and 18 research centers around the globe.

Download or read book Prioritization Optimization Process Algorithm to Manage Pavement Networks During the Non Availability of Historical Data written by A. Kitaha and published by . This book was released on 2016 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt: A common practice followed to rate the pavement surface condition is to use the ASTM D5340-12 procedure and estimate the pavement condition index (PCI) that helps prioritize maintenance needs and assists developing a pavement management system (PMS). However, ASTM-PCI that is dependent on time-based evaluation may not be suitable where there is a lack of historical records and it is being undertaken for the first time. To estimate a pavement's current PCI during the non-availability of historical data and establish a PMS incorporated with prioritized maintenance and optimized budget, a rational engineering criteria (EC) based methodological approach is required that is as robust as ASTM D5340-12. Thus, the objective of this study was to develop a rational EC-based prioritization-optimization process PMS (POPMS) algorithm for a network that prioritizes maintenance strategies for identified pavement distresses and hence optimizes maintenance costs depending on budgetary allocations. An EC-based POPMS algorithm was based on a network length of 100.55 km, which followed prioritization-optimization process for single to multi-year programs. EC-PCI of pavement sections were estimated on the basis of segmented maintenance strategies including preventive and routine maintenance and reconstruction. EC-PCI was found to be rational since three distinct threshold zones were considered that could directly assign pavement maintenance strategies, which was straightforward and circularly referenced. Overall, POPMS algorithm facilitates practitioners to modify the threshold EC-based parameters that will estimate an optimal single/multiyear budget for maintenance as per the newly set threshold level, thus creating a whole new promising approach in the areas of roadway network level maintenance programs.

Download or read book Pavement Asset Management written by Ralph Haas and published by John Wiley & Sons. This book was released on 2015-05-26 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive and practical, Pavement Asset Management provides an essential resource for educators, students and those in public agencies and consultancies who are directly responsible for managing road and airport pavements. The book is comprehensive in the integration of activities that go into having safe and cost-effective pavements using the best technologies and management processes available. This is accomplished in seven major parts, and 42 component chapters, ranging from the evolution of pavement management to date requirements to determining needs and priority programming of rehabilitation and maintenance, followed by structural design and economic analysis, implementation of pavement management systems, basic features of working systems and finally by a part on looking ahead. The most current methodologies and practical applications of managing pavements are described in this one-of-a-kind book. Real world up-to-date examples are provided, as well as an extensive list of references for each part.

Download or read book Development of Empirical and Mechanistic Empirical Performance Models at Project and Network Levels written by Amr Ayed and published by . This book was released on 2016 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Performance prediction models are a vital component in pavement management systems (PMS). Along with decision trees, prediction models are used to set priorities for maintenance and rehabilitation planning, and ultimately for budget allocations at the network level. Reliable and accurate prediction of pavement deterioration over time helps transportation agencies accurately predict future spending and save significant amounts of money. Within a PMS, raw performance data is often converted into aggregated performance indices, such as the Riding Comfort Index (RCI), to quantify the road's roughness, or the Distress Surface Index (SDI), to quantify accumulated pavement distress. Technology has evolved rapidly in the last two decades, making data collection for pavement conditions (i.e. roughness and distress data) more feasible for transportation agencies. However, transportation agencies, especially at the municipal level, only maintain condition data to evaluate the present pavement status. Only limited attempts have so far been made to develop or enhance existing deterioration models in pavement management systems, using periodically collected condition data over time. A well-maintained historical database of pavement condition measurements and performance indices can be a useful source for the development of performance prediction models. In some cases, however, the database may contain incomplete data and insufficient information to develop reliable performance models. In addition to inconsistency in the historical performance data, the age of the pavement or the date of the last maintenance/ rehabilitation treatment may not be available to develop the pavement performance over time. The goal of this research is to develop enhanced empirical performance models capable of capturing the unpredictable and indeterminate nature of pavement deterioration behavior. This research provides a methodology to develop empirical models in the absence of the construction and/or rehabilitation dates. The models developed in this research use limited available historical data, and examine different parameters, such as pavement thickness, traffic pattern, and subgrade condition. Parameters such as the date of pavement construction and the age of the pavement are also incorporated into the proposed models, and are constrained by local experience and engineering judgment. A linear programming optimization technique is employed to develop the empirical models presented in this research. The approach demonstrated in this research can also be expanded to account for additional parameters, and can easily be adapted to match the needs of different agencies based on their local experience. In addition, the current research develops a second set of deterioration models based on mechanistic-empirical principles. Models incorporated into the mechanistic-empirical design guide are locally calibrated. A genetic algorithm optimization technique is employed to guide the calibration process, in order to determine the coefficients that best represent pavement performance over time. The two sets of performance models developed in this research are compared at both the project and network level of analysis. A decision-making framework is implemented to incorporate the two sets of models, and a comprehensive life cycle cost analysis is carried out to compare design alternatives in the project level analysis. The two model sets are also evaluated at the network level analysis using a municipal pavement management system. Two budget scenarios are executed, based on the developed performance models, and a comparison between network performance and budget spending is presented. Finally, a summary and current research contribution to the pavement industry will be presented, along with recommendations for future research.

Download or read book Bearing Capacity of Roads Railways and Airfields written by Andreas Loizos and published by CRC Press. This book was released on 2017-07-20 with total page 3209 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bearing Capacity of Roads, Railways and Airfields includes the contributions to the 10th International Conference on the Bearing Capacity of Roads, Railways and Airfields (BCRRA 2017, 28-30 June 2017, Athens, Greece). The papers cover aspects related to materials, laboratory testing, design, construction, maintenance and management systems of transport infrastructure, and focus on roads, railways and airfields. Additional aspects that concern new materials and characterization, alternative rehabilitation techniques, technological advances as well as pavement and railway track substructure sustainability are included. The contributions discuss new concepts and innovative solutions, and are concentrated but not limited on the following topics: · Unbound aggregate materials and soil properties · Bound materials characteritics, mechanical properties and testing · Effect of traffic loading · In-situ measurements techniques and monitoring · Structural evaluation · Pavement serviceability condition · Rehabilitation and maintenance issues · Geophysical assessment · Stabilization and reinforcement · Performance modeling · Environmental challenges · Life cycle assessment and sustainability Bearing Capacity of Roads, Railways and Airfields is essential reading for academics and professionals involved or interested in transport infrastructure systems, in particular roads, railways and airfields.

Download or read book Harmonization of Different Types of Network level Pavement Management Systems written by and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The priority assessment analysis method, as a part of a Pavement Management System, is the most appropriate one for short and medium term road network improvement planning, while the network optimization methods serve for the long term policy defining. Their optimization criteria are expressed in different terms. Both systems may represent two stages of a unique planning process - a conceptual and a detailed one. To use these systems for such purposes their results must be compatible. Optimal strategies from both investors and users points of view, obtained by the network optimisation method, were introduced into HDM - III, avoiding the Expenditure budgeting Model (EBM). All the results were translated into the same units or criteria. The predicted effects, especialy those that consider the use of available resources, were better than those obtained by the standard procedure. The relations between the users and the agency costs for different traffic categories and budgeting levels were observed. Such an approach meets the needs of networks which are far from an optimal steady state. For the covering abstract of this conference see IRRD number 872978. (A.

Download or read book Developing a Network Optimization Model for Pavement Management Using Dynamic Programming written by Omar Ghaleb Smadi and published by . This book was released on 1993 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Multi period Optimization of Pavement Management Systems written by Jaewook Yoo and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this research is to develop a model and solution methodology for selecting and scheduling timely and cost-effective maintenance, rehabilitation, and reconstruction activities (M & R) for each pavement section in a highway network and allocating the funding levels through a finite multi-period horizon within the constraints imposed by budget availability in each period, frequency availability of activities, and specified minimum pavement quality requirements. M & R is defined as a chronological sequence of reconstruction, rehabilitation, and major/minor maintenance, including a "do nothing" activity. A procedure is developed for selecting an M & R activity for each pavement section in each period of a specified extended planning horizon. Each activity in the sequence consumes a known amount of capital and generates a known amount of effectiveness measured in pavement quality. The effectiveness of an activity is the expected value of the overall gains in pavement quality rating due to the activity performed on a highway network over an analysis period. It is assumed that the unused portion of the budget for one period can be carried over to subsequent periods. Dynamic Programming (DP) and Branch-and-Bound (B-and-B) approaches are combined to produce a hybrid algorithm for solving the problem under consideratioin. The algorithm is essentially a DP approach in the sense that the problem is divided into smaller subproblems corresponding to each single period problem. However, the idea of fathoming partial solutions that could not lead to an optimal solution is incorporated within the algorithm to reduce storage and computational requirements in the DP frame using the B-and-B approach. The imbedded-state approach is used to reduce a multi-dimensional DP to a one-dimensional DP. For bounding at each stage, the problem is relaxed in a Lagrangean fashion so that it separates into longest-path network model subproblems. The values of the Lagrangean multipliers are found by a subgradient optimization method, while the Ford-Bellman network algorithm is employed at each iteration of the subgradient optimization procedure to solve the longest-path network problem as well as to obtain an improved lower and upper bound. If the gap between lower and upper bound is sufficiently small, then we may choose to accept the best known solutions as being sufficiently close to optimal and terminate the algorithm rather than continue to the final stage.