F. Jordan Srour

Learning Curves in Construction: A Critical Review and New Model

AbstractThis paper brings forth from the literature a series of learning curve models and evaluates them through the lens of the construction industry. The review suggests that there is still no consensus on which model provides the best fit and predictability for construction data. As such, this paper puts forth a new model that is suitable for the modern construction industry as it accommodates for both mechanization and forgetting. The proposed model is similar to the Wright model (an exponential model of learning), but, through recursion, places more emphasis on recent data. The proposed model shows an error of less than 1% when predicting the cumulative average completion times in three out of four cases examined.

A case study in model selection for policy engineering: simulating maritime customs

The progress of containers through customs is more often an exercise in negotiation rather than a structured queuing process. As soon as a regulatory process involves negotiation, corruption becomes a factor. Studies by the Organization for Economic Co-operation and Development (OECD) and other organizations reveal that customs corruption is not easily combated by policy changes. Simulation of potential reform policies in the maritime customs context can provide insights for decision makers. In this paper we present a work-in-progress case study of simulation technique selection for modelling social complexity in the domain of maritime customs. We give evidence (1) to the applicability of a methodological approach that includes evaluation and reasoned selection of a modelling paradigm, and (2) to the applicability of agent-based simulation.

A survey of absenteeism on construction sites

Purpose The construction industry is dynamic and often unregulated due to its complex, project-based nature. This makes the task of implementing human resource management (HRM) functions more difficult than in other economic sectors. This is particularly the case for developing countries which rely on a migrant, casual, and transient workforce. Despite offering flexibility, a transient workforce can lead to unpredictable rates of absenteeism and unsatisfactory productivity. This paper links HRM practices in the construction industry of the developing world to rates of absenteeism across three segments of the construction workforce – foremen, skilled workers, and unskilled workers. The paper aims to discuss these issues. Design/methodology/approach A survey targeting 60 construction sites in Beirut, Lebanon form the basis of the analysis. Within each site, measures of absenteeism for foremen, skilled, and unskilled workers were solicited along with other data on HRM onsite. Findings The results suggest a regression model for worker absenteeism based on tenure of work as well as the absenteeism of workers at the next hierarchical level onsite. Originality/value This study is among the first to show a link between the mechanisms by which construction workers are employed (contract-based foremen vs daily/weekly labourers – both skilled and unskilled) and the rate of absenteeism seen onsite. Given the role of absenteeism in construction productivity, having a good understanding of the underlying causes of absenteeism is critical to the design of mitigating policies.

Using simulation to evaluate how multi-agent transportation planners cope with truck breakdowns

In most real-world settings, a transportation plan requires modifications during execution. A thorough evaluation of transportation planning methods thus requires testing and comparison in a dynamic environment. We give conditions on a simulation environment that follow from this requirement, and propose a multi-agent simulator meeting these conditions. In addition, we propose a new measure that captures robustness in such dynamic settings. The multi-agent simulator and the robustness measure are then used to compare three different transportation methods (two multi-agent planners and one online optimization approach) in settings with release time uncertainty and truck breakdown incidents.

Integrating Data Collection Optimization into Pavement Management Systems

This paper describes a method for using location data to optimize the routing of pavement data collection vehicles. In much of the developed world, pavement testing is performed on a regular basis; the pavement testing data, in turn, serves as input to Pavement Management Systems. Currently, in the United States of America, state departments of transportation plan this data collection work by providing the list of roads that must be tested and then leave the routing of the vehicles to the equipment operators who typically execute the work in an ad hoc manner. This study presents the processes required to code the list of roads for testing, select appropriate hotels in the region of testing, and apply a Traveling Salesman Problem with Hotel Stops model to derive a route. Applying the processes to a case study shows significant cost savings associated with this method of roadway testing, as opposed to the current ad hoc methods.

An Initial Study of Agent Interconnectedness and In-Group Behaviour

This paper asks whether agent-based simulation can give insight into social factors surrounding corrupt behaviour in a technical process. The specific case study adopted, for studying the effects of social interconnectedness on corrupt behaviours, is the domain of maritime customs. Taking our previously-developed agent-based simulation, we add to the simulation a nuanced model of actor relatedness, consisting of clan, in-group (sect), and town of origin, and encode selected behavioural norms associated with these factors. Using the simulation, we examine the effects of social interconnectedness on domain performance metrics such as container outcomes, time, revenue, coercive demands, and collusion. Initial results confirm that as actor interconnectedness increases, established policies to combat corruption, such as process re-engineering, become less effective.

Using ABM to Evaluate the Impact of Social Networks on Construction Labor Productivity

Labour productivity depends on a wide variety of factors, some of which pertain to characteristics of the construction crews themselves. Several of these factors such as language and demographics are described in the literature as soft or intangible and are of stochastic nature. As such, traditional deterministic modelling techniques are not sufficient to capture the full picture of the factors that come into play when considering construction labour productivity. Agent based modelling (ABM), a simulation technique with growing popularity, presents a powerful candidate for modelling construction sites due to its properties and ability to consider social aspects. This paper demonstrates that ABM is an acceptable paradigm for studying the effect of both tangible and soft features on construction labour productivity.

Using Optimization to Manage Quarries in the Recycling of Construction and Demolition Waste

The construction industry consumes large amounts of aggregates, sand, and stone causing a strain on the limited sources of these natural materials (i.e., quarries). The industry is also a major source of waste. Waste, commonly referred to as Construction and Demolition Waste (C&DW), is generated at various stages of construction and in demolition processes. Increased construction activities and limited landfill space have encouraged efforts to divert C&DW away from landfills to sorting, recycling, and reusing. While these efforts have been successful in some countries (e.g., Germany, Netherlands), developing countries such as Lebanon suffer from illegal and haphazard dumping of C&DW. This paper reports on an ongoing research project which investigates synergies between two elements of the construction industry, C&DW and quarries. The aim is to develop an optimization model that will provide decision support in the selection of a cost and environmentally effective set of abandoned quarries to serve as C&DW landfills, as and processing facilities.

Strategies for Handling Temporal Uncertainty in Pickup and Delivery Problems with Time Windows

In many real-life routing problems there is more uncertainty with respect to the required timing of the service than with respect to the service locations. We focus on a pickup and delivery problem with time windows in which the pickup and drop-off locations of the service requests are fully known in advance, but the time at which these jobs will require service is only fully revealed during operations. We develop a sample-scenario routing strategy to accommodate a variety of potential time realizations while designing and updating the routes. Our experiments on a breadth of instances show that advance time related information, if used intelligently, can yield benefits. Furthermore, we show that it is beneficial to tailor the consensus function that is used in the sample-scenario approach to the specifics of the problem setting. By doing so, our strategy performs well on instances with both short time windows and limited advance confirmation.

Value of Dynamic Revenue-Maximizing Congestion Pricing in a Highly Congested Corridor

AbstractThis paper examines the value of utilizing dynamic, revenue-maximizing, congestion pricing on a privately operated tolled route, when the only alternative is a highly congested, public, free-access route. Three methods are specified by which revenue can be maximized—through the selection of a fixed percent of users to set the toll price for, through the selection of a fixed level of service on the toll road, and through the use of a nonlinear optimization model. These methods are tested on a case study involving a highly congested corridor. In simulation, the corridor’s flow rates are observed following the posting of a toll, the toll is updated, and the new flow observed until a subsequent round of revenue maximizing is applied to the new conditions. It was concluded that in a highly congested corridor a dynamic, revenue-maximizing toll can finance the construction of new capacity without degrading social welfare.