This study uses agent-based modeling as a proof of concept tool to investigate the applicability of the green performance bond framework to provide insights into the potential benefits of implementing it within the construction industry. The research also evaluates its feasibility and effectiveness in discouraging opportunistic bidding behaviors.
A steel stock yard for storing the purchased steel plates is the first step of shipbuilding. It is also space where sorting is performed to supply proper steel plates to the cutting process at the right time. Usually, it is difficult to supply all steel plates from one steelwork. Therefore, the deviation of the duration of plate procurement increases in the process of supplying steel plates from multiple steelworks. The changes in production plans from this deviation affect the duration for which the steel plates stay in the stock yard.
To address this problem, shipbuilding yards are researching on efficient management of steel plates in a limited space. In this study, a steel stock yard simulation model was constructed using discrete event simulation.
Large-scale events are always vulnerable to natural disasters and man-made chaos which poses great threat to crowd safety. Such events need an appropriate evacuation plan to alleviate the risk of causalities. We propose a modeling framework for large-scale evacuation of pedestrians during emergency situation. Proposed framework presents optimal and safest path evacuation for a hypothetical large-scale crowd scenario. The main aim is to provide the safest and nearest evacuation path because during disastrous situations there is possibility of exit gate blockade and directions of evacuees may have to be changed at run time. The recommended simulation framework incorporates Anylogic simulation environment to design complex spatial environment for large-scale pedestrians as agents.
Using new technologies to maintain, construct, and reuse naturally created products like asphalt, soils, and water can reserve the environment. The objective of this study was to specify and model the behavior of households regarding the installation of water conservation technology and evaluate strategies that could potentially increase water conservation technology adoption at the household level. In particular, this study created an agent-based modeling framework in order to understand various factors and dynamic behaviors affecting the adoption of water conservation technology by households. The model captures various demographic characteristics, household attributes, social network influence, and pricing policies; and then evaluates their influence simultaneously on household decisions in adoption of water conservation technology. The application of the proposed simulation model was demonstrated in a case study of the City of Miami Beach. The simulation results identified the intersectional effects of various factors in household water conservation technology adoption and also investigated the scenario landscape of the adoptions that can inform policy formulation and planning.
Despite a high potential to improve the productivity, quality and safety and also to reduce costs, automated technologies are not widely spread in the construction sector. This paper presents a simulation-based approach to analyze the technical and economic feasibility of wire robots for automated construction in future investigations. Masonry buildings are considered as an appropriate application case due to repetitive construction procedures and high demands concerning accuracy of construction. A simulation model representing the fundamental mechanics of a wire robot is created. Special focus lies on creating collision-free motion profiles which can be exported to the robot control system. BIM models can be used to set-up the simulation model and to prepare the required input data. Following a modular structure, the model can be applied with different purposes in the exploration of the approach. The construction of a one-story masonry building serves as case study proving the concept’s functionality.
The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Although previous research efforts developed models to represent the learning curve effect using traditional simulation approaches such as System Dynamics (SD) and Discrete Event Simulation (DES), none of these studies used Agent-Based Modeling (ABM) techniques. This study takes the initial steps and presents work targeted at analyzing the effect of learning on labor productivity using ABM.
One of the most common operations to any construction project is earthwork. In fact, most, if not all, construction projects begin with earthwork activities. These activities require heavy equipment, are generally quite costly and consume a considerable amount of time.
This research proposes and tests an integrated framework for bottom-up simulation of performance in construction projects. The proposed framework conceptualizes construction projects as systems-of-systems in which the abstraction and micro-simulation of dynamic behaviors are investigated at the base-level consisting of the following elements: human agents, information, and resources.
The offshore wind industry in Europe is looking to move further from shore and increase the size of wind parks and wind turbines. As of now marine logistics during the operation and maintenance life cycle phase is, besides wind turbine reliability, the most important limitation for wind turbine service, repair and replacement, and pose a large risk for wind park operators and owners.
Economic slowdown and construction demand shrinkage reduces the profit backlog for construction contractors and bites into their profit margin. The resulting fierce competition for jobs forces construction companies to look for more sophisticated analytical tools to analyze and improve their bidding strategies. For each contractor, bidding strategy is a decision-making process that is driven by the firm’s financial goals with the final objective of maximizing the firm’s gross profit and surpassing the breakeven point. This paper proposes a methodology to model and analyze different bidding strategies with hybrid agent based-system dynamics (ABSD) simulation.