Assessment of decision-making factors affecting dump truck allotment: An artificial neural network approach

• Main Authors: Ongpeng, Jason Maximino C., Alimon, Catherine P., Lumanlan, Raymund Francis D., Macabagdal, Jommel R.
• Format: text
• Published: Animo Repository 2007
• Subjects: Resource allocation; Project management; Neural networks (Computer science); Construction Engineering and Management
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/8871
• Institution: De La Salle University

This research paper deals with the assessment of decision-making factors affecting dump truck allotment in the construction of gasoline service stations in the Philippines. Such factors considered in this study were the following: (a) location of project site, (b) project duration, (c) distance of the source materials (such as soil) from the project site, (d) volume of backfill, (e) depth of backfill and (f) total project lot area. The authors utilized the supervised network approach in artificial neural analysis using the Learning Vector Quantization (LVQ) technique in order to recognize patterns among the most significant decision-making factors mentioned above so as to arrive with the best pattern-based mathematical model that the authors employed to compute for the necessary number of dump trucks to be allotted on a project site.