Gunnar Lucko

Research Validation: Challenges and Opportunities in the Construction Domain

Validation of the research methodology and its results is a fundamental element of the process of scholarly endeavor. Approaches used for construction engineering and management research have included experiments, surveys and observational studies, modeling and simulation, theory building, case studies, and various subtypes thereof. Some studies use more than one approach. A particular contribution of this paper is that it reviews different types of validation using examples of studies, analyzes the specific challenges that were found to be significant, and presents how they were successfully overcome in each case. Another contribution is that it describes new opportunities for research validation that are emerging at the horizon as well as ongoing collaborative efforts to enhance the access of construction researchers to validation tools. This paper increases the awareness of the paramount role that validation techniques play in scholarly work by providing readers with recommendations to properly validate their own research efforts.

Productivity Scheduling Method: Linear Schedule Analysis with Singularity Functions

This paper describes a new integrated method of linear schedule analysis using singularity functions. These functions have previously been used for structural analysis and are newly applied to scheduling. Linear schedules combine information on time and amount of work for each activity. A general model is presented with which activities and their buffers can be mathematically described in detail. The algorithm of the new method forms the body of the paper, including the steps of setting up initial equations, calculating pairwise differences between them, differentiating these to obtain the location of any minima, and deriving the final equations. The algorithm consolidates the linear schedule under consideration of all constraints and, thus, automatically generates the minimum overall project duration. The model distinguishes time and amount buffers, which bears implications for the definition and derivation of the critical path. Future research work will address float and resource analysis using the new model. DOI: 10.1061/ ASCE 0733-9364 2009 135:4 246 CE Database subject headings: Scheduling; Critical path method; Network analysis; Geometry; Time dependence; Productivity.

Float Types in Linear Schedule Analysis with Singularity Functions

This paper describes how float can be calculated exactly for linear schedules by using singularity functions. These functions originate in structural engineering and are newly applied to scheduling. They capture the behavior of an activity or buffer and the range over which it applies and are extensible to an infinite number of change terms. This paper builds upon the critical path analysis for linear schedules, which takes differences between singularity functions and differentiates them. It makes several important case distinctions that extend the earlier concept of rate float. Time and location buffers act along different axis directions. Together with different productivities between and within activities, this can create a complex pattern of critical and noncritical segments. Depending on starts and finishes, areas of float precede or follow these noncritical segments. The schedule of a small project is reanalyzed with case distinctions to demonstrate in detail what float types are generated.

Integrating Efficient Resource Optimization and Linear Schedule Analysis with Singularity Functions

Resources perform or enable physical operations and thus are vital on construction projects, yet are subject to various constraints. Their use within a project schedule must therefore be carefully planned. A major objective is optimizing when they are active within the float of noncritical activities to avoid disruptive and costly fluctuations. This paper builds on analyzing criticality of linear schedules with the unique singularity functions. The new approach keeps resources intact and derives one flexible equation for the complete resource profile of a schedule, including any timing or resource rate changes. Another equation models its first moment of area to minimize the objective function toward a level profile. A genetic algorithm is suitable for an iterative optimization. The parameters of its chromosomes are recombined evolutionarily and can model any permutation. Analyzing a road project illustrates how singularity functions integrate resource optimization with its linear schedule and facilitate a subsequent optimization.

Optimizing Cash Flows for Linear Schedules Modeled with Singularity Functions by Simulated Annealing

The ability of construction contractors to plan and manage cash flow is critical for their economic success. The cumulative interaction of outflows (labor, materials, and equipment costs) and inflows (progress payments less retainage) creates a profile with a complex zigzag shape. This could only be modeled by simplification, e.g., as values tabulated at discrete times; averaged S-curves without peaks; or envelopes of all possible constellations. Neither is suited for a fully integrated model that dynamically links schedules with their cash flows for optimization. Therefore, singularity functions, whose components define ranges of behavior between cutoffs, are used to flexibly yet accurately model cash flow profiles and their various payment terms. The new approach augments construction project management toward an integrated planning model and is validated with an example from the literature. Optimization with a simulated annealing algorithm shifts activity positions in a randomized but directed search f...

Flexible modeling of linear schedules for integrated mathematical analysis

Developing and analyzing schedules is essential for successfully controlling the time aspect of construction projects. The critical path method of scheduling is by far the most widely use scheduling technique in the construction industry. However, several problems related to its concept and use have been identified in the literature. The lesser known linear scheduling method has much potential for handling the rich information that project managers handle on a daily basis. While being well-suited to linear and repetitive projects, it has been a predominantly graphical method without a comprehensive underlying mathematical model. This paper introduces a new method based on singularity functions using Macaulay bracket notation. It makes beneficial use of the strengths of these functions, including their flexibility and clarity, while remaining intuitive and requiring only basic geometry and algebra knowledge from users. An example from the literature is re-analyzed step-by-step and compared successfully with the critical path method.

Challenges and opportunities for productivity improvement studies in linear, repetitive, and location-based scheduling

Despite theoretical advancements in alternative project planning methods the extent of their practical implementation varies strongly; it has been limited especially in the US construction industry. The family of linear, repetitive, and location-based scheduling techniques holds significant but barely substantiated promise by containing multiple variables of interest for integrated analysis and optimization. Yet it is necessary to provide empirical evidence that using such techniques can improve productivity to increase credibility and acceptance by practitioners, because claims of conceptual superiority are only sporadically supported with detailed measures. An analysis is performed to identify relevant decision-making variables, extract challenges that currently limit the corpus of quantitative productivity studies on alternative scheduling to its insufficient size, and reveal opportunities to expand it in breadth and depth. Variables are categorized by their relevance to time, activity, resource and location, as well as the managerial approach. Challenges include the diverse definitions of productivity itself, issues related to achieving generalizability, and the detailed steps of data collection, preparation, and analysis. Opportunities include the guidance from existing but rare studies and well-established research methods such as case studies that can be applied. This is illustrated with a sample project of a high-rise apartment building in Brazil. If alternative methods can be proven to be measurably better for specific applications, there might be a paradigm shift from merely defaulting to traditional but problematic network-based scheduling toward consciously choosing the planning method based on its potential benefits for a project.

Quantitative Research: Preparation of Incongruous Economic Data Sets for Archival Data Analysis

In the field of construction engineering and management, archival data sets are not always as correct and consistent as it would be desirable. Between different sources that are studied, e.g., companies, they may differ in format or content and within them, they may still be incongruous and require substantial preparation. This makes examining theories and extracting trends from historic data more difficult than it is for carefully controlled experimental studies or for collecting new data. The purpose of this paper is not to review the regression models that the writers developed during their research, but to focus on the data preparation that had to be applied before those analyses. The objective is to outline various techniques that can be applied to archival data that are related to construction engineering and management to give researchers a set of best practices on data preparation that can assist them in gleaning truths from them.

Harnessing the power of simulation in the project management/decision support aspects of the construction industry

This paper reviews the history of construction simulation systems in light of their graphical representation of complex scenarios. The simulation of construction operations has been a growing field of research over the last several decades. Since the introduction of the first simulation system, which was based on the activity cycle diagram paradigm of modeling, numerous additional tools have been introduced, each building on and expanding the modeling and analytical capabilities of previous approaches. However, despite such rich body of knowledge, which by now is expanding into areas such as visualization, animation, and virtual reality applications for construction project management, the beneficial application of simulation in practice has been marginal. This paper describes both historical and practical reasons for this situation and presents an ontology-based approach that can harness existing information in construction project management, especially the scheduling function, and has the potential to significantly improve its operational planning and optimization.

Rapid deployment of simulation models for building construction applications

This paper presents a knowledge based approach to increase the use of simulation in the construction industry without its users having to become or hire experts in simulation techniques. The premise of this approach is to use existing process-related schedule information as inputs to create a functioning simulation model with little or no user intervention. It explains analytical capabilities and limitations of schedules and simulation, reviews previous discrete event simulation studies, and discusses integrating knowledge from this domain. It describes the architecture of the WorkSim® system. A case study presents processes of a real construction project. The conceptual and pragmatic feasibility of converting schedules into simulations is tested with its representative sample dataset. Modeling and analyzing this case study establishes the technical viability of the ideas discussed in the paper. Future work will examine challenges to the quality of such models, e.g. their resolution, required resource data, and duration distributions.