Abstract: Construction projects are information intensive in
nature and involve many activities that are related to each other.
Wireless technologies can be used to improve the accuracy and
timeliness of data collected from construction sites and shares it with
appropriate parties. Nonetheless, the construction industry tends to be
conservative and shows hesitation to adopt new technologies. A main
concern for owners, contractors or any person in charge on a job site
is the cost of the technology in question. Wireless technologies are
not cheap. There are a lot of expenses to be taken into consideration,
and a study should be completed to make sure that the importance
and savings resulting from the usage of this technology is worth the
expenses. This research attempts to assess the effectiveness of using
the appropriate wireless technologies based on criteria such as
performance, reliability, and risk. The assessment is based on a utility
function model that breaks down the selection issue into alternatives
attribute. Then the attributes are assigned weights and single
attributes are measured. Finally, single attribute are combined to
develop one single aggregate utility index for each alternative.
Abstract: Evolutionary optimization methods such as genetic
algorithms have been used extensively for the construction site layout
problem. More recently, ant colony optimization algorithms, which
are evolutionary methods based on the foraging behavior of ants,
have been successfully applied to benchmark combinatorial
optimization problems. This paper proposes a formulation of the site
layout problem in terms of a sequencing problem that is suitable for
solution using an ant colony optimization algorithm.
In the construction industry, site layout is a very important
planning problem. The objective of site layout is to position
temporary facilities both geographically and at the correct time such
that the construction work can be performed satisfactorily with
minimal costs and improved safety and working environment. During
the last decade, evolutionary methods such as genetic algorithms
have been used extensively for the construction site layout problem.
This paper proposes an ant colony optimization model for
construction site layout. A simple case study for a highway project is
utilized to illustrate the application of the model.
Abstract: Roadway planning and design is a very complex
process involving five key phases before a project is completed;
planning, project development, final design, right-of-way, and
construction. The planning phase for a new roadway transportation
project is a very critical phase as it greatly affects all latter phases of
the project. A location study is usually performed during the
preliminary planning phase in a new roadway project. The objective
of the location study is to develop alignment alternatives that are cost
efficient considering land acquisition and construction costs. This
paper describes a methodology to develop optimal preliminary
roadway alignments utilizing spatial-data. Four optimization criteria
are taken into consideration; roadway length, land cost, land slope,
and environmental impacts. The basic concept of the methodology is
to convert the proposed project area into a grid, which represents the
search space for an optimal alignment. The aforementioned
optimization criteria are represented in each of the grid’s cells. A
spatial-data optimization technique is utilized to find the optimal
alignment in the search space based on the four optimization criteria.
Two case studies for new roadway projects in Duval County in the
State of Florida are presented to illustrate the methodology. The
optimization output alignments are compared to the proposed Florida
Department of Transportation (FDOT) alignments. The comparison is
based on right-of-way costs for the alignments. For both case studies,
the right-of-way costs for the developed optimal alignments were
found to be significantly lower than the FDOT alignments.