Data acquisition technologies for construction progress tracking

Infrastructure assets, serving everyone’s daily life, are an essential foundation of any society. Their management faces a wide range of challenges. Hence optimization methods are increasingly applied to assist making management decisions in infrastructure asset management (IAM). A large number of articles apply a broad range of optimization methods in their decision making (DM) and achieve great results. However, they mainly focus on individual methods and a comprehensive knowledge, given the broad range of optimization methods, is hardly discussed. Hence it is valuable to analyze and graphically present the existing knowledge on this subject. This paper, based on a total of 337 articles, provides an overall review of the applications of optimization when making management decisions in IAM, with the intension of enhancing the optimization application and method selection and guiding the future research in this field. More specifically, this paper introduces the application process of optimization when assisting DM in IAM, summarizes the previous application research, and discusses the popular optimization methods applied in DM in IAM. According to the literature review, this paper confirms optimization can effectively assist DM in IAM and a wide range of optimization methods are applicable to assist a variety of DM problems. The recommendations on the applications and selection of optimization methods in the context of IAM are also made to facilitate the applications.

Optimization in Decision Making in Infrastructure Asset Management: A Review

Multi-objective optimization for pavement maintenance and rehabilitation decision-making: A critical review and future directions

In 2007, Executive Order 13423 mandated 30% energy and emission reductions for all government facilities by 2015. Unfortunately, the government fell short of their goal by 9%. Their approach through mandates and federal legislation focused predominantly on new construction and major retrofits to existing facilities. To meet future energy and emission reduction goals, more emphasis on facility management is needed. The government manages over 370 million square feet of facilities each year. The daily decision process for government facility managers is full of competing interests, such as maintenance needs (preventative and corrective), limited operating budgets, time constraints to make decisions, and bounded rationality about energy consumption and savings. By understanding how these decisions are made and the cognitive bias that may occur, advances in facility management decision making can reduce energy consumption. Cognitive biases to the decision making process such as loss aversion, anchoring, and status quo bias are explored and an approach to overcome them is offered, a tactic called choice architecture, meaning restructuring decision environments to align with behavioral decision theory. Examples of choice architecture, such as, enabling procurement systems to query green products, changing default settings in mechanical systems, and requiring the use of pay back period calculators to account for cognitive limitations of the decision maker, are suggested and supported by behavioral science research to help direct facility managers towards energy efficient choices. This approach, through choice architecture, holds potential to yield relatively low-cost solutions (they do not require new mandates or laws) to support greater energy reduction in government facility management. This merging of literature from behavioral science to facility management is meant to open new avenues of interdisciplinary research.

Opportunities for greater energy efficiency in government facilities by aligning decision structures with advances in behavioral science

It is paramount to perform timely and appropriate maintenance actions on networked infrastructures, such as power transmission, transportation, telecommunications, and so forth, in order to ensure ...

Joint optimization of maintenance planning and workforce routing for a geographically distributed networked infrastructure

Purpose – This paper aims at improving progress tracking and control of repetitive projects by developing a novel framework that automates the documentation of as-built information directly into the project schedule and also introduces enhanced linear scheduling formulation to support project control decisions. Design/methodology/approach – The proposed framework uses e-mail technology to facilitate detailed tracking of daily as-built events of all parties through bidirectional communication between site and head office. It also provides a new formulation for more accurate critical path and linear scheduling computation to accurately update the project's time and cost during construction. Findings – Using a case study of a road project, the paper proves that the proposed framework reduces as-built documentation effort and its schedule updates are more responsive to all as-built events than traditional scheduling techniques. Research limitations/implications – The proposed method applies to linear projects...

Framework for enhanced progress tracking and control of linear projects

Infrastructure fund-allocation is a complex multi-dimensional decision-making problem. It involves multiple stakeholders, thousands of assets with multiple alternative renewal types and timings for each intervention over the planning horizon. Decision-makers need to satisfy stakeholders’ preferences, and determine which and when assets will be funded (network-level decisions) and what repair strategy to use for each asset (project-level decisions). Most of the existing research efforts that addressed both levels have suffered from: consideration of a single objective, fragmented optimisation formulation, and scalability issues in handling large networks of assets. Accordingly, a concurrent bilevel optimisation model that combines both levels into one mathematical formulation while satisfying the varying objectives of infrastructure stakeholders is developed. A pavement case study is used to evaluate its performance against existing phased techniques. Afterwards, two multi-objective formulations ha...

Concurrent bilevel multi-objective optimisation of renewal funding decisions for large-scale infrastructure networks

Whereas extensive literature exists on repetitive scheduling to help projects benefit from repetition and resource continuity, its underlying formulations suffer from serious challenges tha...

Enhanced Repetitive-Scheduling Computation and Visualization

This paper presents a hands-on exercise on construction project management to augment traditional teaching methods and help students improve their construction experience and project management skills. The exercise involved 100 students participating in managing and constructing a 3.8-m (12.5-ft) model of Canada’s CN Tower within a 30-min deadline. Before construction, the groups prepared method statements, cost estimates, and schedules for constructing the model. During construction, the groups had to manage limited resources, procurement challenges, and forced interruptions to keep the project on track. To experience new project-tracking methods, students were introduced to a voice-based prototype for collecting progress information and automatically updating the schedule. The results indicate that students gained better understanding of the real construction environment and how to apply their acquired construction management skills to handle the involved complexities and interdependencies. The ...

Hands-On Exercise for Enhancing Students’ Construction Management Skills

Purpose – The purpose of this paper is to propose a microeconomic-based approach to support fund-allocation decisions for a large number of assets. Under the prevailing financial constraints and rapid deterioration of facilities, arriving at optimum fund allocation for capital renewal projects has become very challenging. Due to the complexity of modeling multi-year life cycle cost analysis, existing fund-allocation methods have serious drawbacks when handling a large portfolio of assets, and their results are difficult to justify. Design/methodology/approach – This paper adopts well-established theories from microeconomics and proposes a new microeconomic-based decision support framework that has two novel components: a heuristic procedure to optimize and justify fund-allocation decisions by balancing the funding among the different asset categories; and a visual what-if analysis approach inspired by the economic indifference maps. Findings – Applying the proposed framework on a real case study of 800 bu...

Dina A. Saad

Papers

Framework for enhanced progress tracking and control of linear projects

Concurrent bilevel multi-objective optimisation of renewal funding decisions for large-scale infrastructure networks

Enhanced Repetitive-Scheduling Computation and Visualization

Hands-On Exercise for Enhancing Students’ Construction Management Skills

Microeconomic optimization and what-if analysis for facilities renewal