Abstract: An appropriate project delivery system (PDS) is crucial
to the success of a construction projects. Case-based Reasoning (CBR)
is a useful support for PDS selection. However, the traditional CBR
approach represents cases as attribute-value vectors without taking
relations among attributes into consideration, and could not calculate
the similarity when the structures of cases are not strictly same.
Therefore, this paper solves this problem by adopting the Relational
Case-based Reasoning (RCBR) approach for PDS selection,
considering both the structural similarity and feature similarity. To
develop the feature terms of the construction projects, the criteria and
factors governing PDS selection process are first identified. Then
feature terms for the construction projects are developed. Finally, the
mechanism of similarity calculation and a case study indicate how
RCBR works for PDS selection. The adoption of RCBR in PDS
selection expands the scope of application of traditional CBR method
and improves the accuracy of the PDS selection system.
Abstract: Earthmoving operations are a major part of many
construction projects. Because of the complexity and fast-changing
environment of such operations, the planning and estimating are
crucial on both planning and operational levels. This paper presents
the framework ofa microscopic discrete-event simulation system for
modeling earthmoving operations and conducting productivity
estimations on an operational level.A prototype has been developed
to demonstrate the applicability of the proposed framework, and this
simulation system is presented via a case study based on an actual
earthmoving project. The case study shows that the proposed
simulation model is capable of evaluating alternative operating
strategies and resource utilization at a very detailed level.
Abstract: Optimal design of structure has a main role in reduction of material usage which leads to deduction in the final cost of construction projects. Evolutionary approaches are found to be more successful techniques for solving size and shape structural optimization problem since it uses a stochastic random search instead of a gradient search. By reviewing the recent literature works the problem found was the optimization of weight. A new meta-heuristic algorithm called as Cuckoo Search (CS) Algorithm has used for the optimization of the total weight of the truss structures. This paper has used set of 10 bars and 25 bars trusses for the testing purpose. The main objective of this work is to reduce the number of iterations, weight and the total time consumption. In order to demonstrate the effectiveness of the present method, minimum weight design of truss structures is performed and the results of the CS are compared with other algorithms.
Abstract: Object-oriented simulation is considered one of the most sophisticated techniques that has been widely used in planning, designing, executing and maintaining construction projects. This technique enables the modeler to focus on objects which is extremely important for thorough understanding of a system. Thus, identifying an object is an essential point of building a successful simulation model. In a maintenance process an object is a maintenance work order (MWO). This study demonstrates a maintenance simulation model for the building maintenance division of Saudi Consolidated Electric Company (SCECO) in Dammam, Saudi Arabia. The model focused on both types of maintenance processes namely: (1) preventive maintenance (PM) and (2) corrective maintenance (CM). It is apparent from the findings that object-oriented simulation is a good diagnostic and experimental tool. This is because problems, limitations, bottlenecks and so forth are easily identified. These features are very difficult to obtain when using other tools.
Abstract: Bidding is a very important business function to find
latent contractors of construction projects. Moreover, bid markup is
one of the most important decisions for a bidder to gain a reasonable
profit. Since the bidding system is a complex adaptive system, bidding
agent need a learning process to get more valuable knowledge for a bid,
especially from past public bidding information. In this paper, we
proposed an iterative agent leaning model for bidders to make markup
decisions. A classifier for public bidding information named PIBS is
developed to make full use of history data for classifying new bidding
information. The simulation and experimental study is performed to
show the validity of the proposed classifier. Some factors that affect
the validity of PIBS are also analyzed at the end of this work.
Abstract: Construction of tunnels is connected with high
uncertainty in the field of costs, construction period, safety and
impact on surroundings. Risk management became therefore a
common part of tunnel projects, especially after a set of fatal
collapses occurred in 1990's. Such collapses are caused usually by
combination of factors that can be divided into three main groups, i.e.
unfavourable geological conditions, failures in the design and
planning or failures in the execution.
This paper suggests a procedure enabling quantification of the
excavation risk related to extraordinary accidents using FTA and
ETA tools. It will elaborate on a common process of risk analysis and
enable the transfer of information and experience between particular
tunnel construction projects. Further, it gives a guide for designers,
management and other participants, how to deal with risk of such
accidents and how to make qualified decisions based on a
probabilistic approach.