Optimizing individual resource assignment using genetic algorithm
Main Article Content
Abstract
Construction activities are mostly determined by the technique known as critical path method (CPM) based on
technical relationships and by resource allocation techniques which is used to examine daily resource requirement.
These resource allocation techniques analyze the overall resource profile of a project without considering working
timetable of any individual resource. Generally, in practice, an assigned foreman designated by a project manager
will be responsible for assigning resources to a particular activity. Most of the time, this assignment is done when
an activity is about to start. Therefore, working timetables of an individual resource cannot be known in advance.
Although most foremen can allocate resources at low cost, there are many occasions that workers are forced to
be idle between jobs or to suddenly change to different tasks. These could result in inefficiency as they affect
workers’ income and their learning process. This paper proposes the use of genetic algorithm technique to assist
in the search for a work plan resulting in the most cost-effective working timetable of an individual resource in a
construction project with unlimited resources. In this study, the efficiency is measured in three dimensions including:
the number of releases and re-hires, the number of resource idle days and the total number of resources required.
To identify the most cost-effective schedule, five different schedules of a project example were generated. They
are 1) early start schedule 2) late start schedule 3) min Mx schedule 4) min RRH schedule and 5) min RID
schedule. Then the respective resource allocations are compared. The results show that, in the case that idle
days were considered unpaid days, the Mx schedule delivered the lowest cost as well as the lowest number of
resource requirement. In the case that resources were paid on idle days, the RID schedule was found to incur the
lowest cost while RRH & RID schedules required the least number of total resources. Based on the study’s
findings, it is recommended that, schedule analysis should be carried out with the planning of the individual
resource timetable to be able to manage project resource efficiently and cost-effectively.
technical relationships and by resource allocation techniques which is used to examine daily resource requirement.
These resource allocation techniques analyze the overall resource profile of a project without considering working
timetable of any individual resource. Generally, in practice, an assigned foreman designated by a project manager
will be responsible for assigning resources to a particular activity. Most of the time, this assignment is done when
an activity is about to start. Therefore, working timetables of an individual resource cannot be known in advance.
Although most foremen can allocate resources at low cost, there are many occasions that workers are forced to
be idle between jobs or to suddenly change to different tasks. These could result in inefficiency as they affect
workers’ income and their learning process. This paper proposes the use of genetic algorithm technique to assist
in the search for a work plan resulting in the most cost-effective working timetable of an individual resource in a
construction project with unlimited resources. In this study, the efficiency is measured in three dimensions including:
the number of releases and re-hires, the number of resource idle days and the total number of resources required.
To identify the most cost-effective schedule, five different schedules of a project example were generated. They
are 1) early start schedule 2) late start schedule 3) min Mx schedule 4) min RRH schedule and 5) min RID
schedule. Then the respective resource allocations are compared. The results show that, in the case that idle
days were considered unpaid days, the Mx schedule delivered the lowest cost as well as the lowest number of
resource requirement. In the case that resources were paid on idle days, the RID schedule was found to incur the
lowest cost while RRH & RID schedules required the least number of total resources. Based on the study’s
findings, it is recommended that, schedule analysis should be carried out with the planning of the individual
resource timetable to be able to manage project resource efficiently and cost-effectively.
Article Details
How to Cite
Kangpanit, C., & Kusalasai, S. (2013). Optimizing individual resource assignment using genetic algorithm. Engineering and Applied Science Research, 40(1), 105–116. Retrieved from https://ph01.tci-thaijo.org/index.php/easr/article/view/8572
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Section
ORIGINAL RESEARCH
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