Abstract:
Borehole drilling is one of the geotechnical investigations for foundation designing process of the construction industry. The growth ofthe construction industry requires an effective utilization of borehole drilling teams for the borehole drilling sites. It is similar to sending multiple travelling salesmen for multiple locations under the minimum over all travelling distance. In the borehole drilling, there are mainly two types of borehole drilling teams: wash boring teams and wash boring/ core drilling teams. And there are different accessible time periods for the sites. The service time of the locations are different and it can be predefined from the nature (number of holes, ground conditions, drilling length... etc.) of the drilling site job. It is expected that the difference ofthe total work duration among teams should be in an accepted level of difference. The research outcome was an algorithm to provide a heuristic solution, answering which team does which job and when it is. Initially, filtering the job list was done, to group similar type ofjobs together and, then groups the jobs, which require completion before the shutdown of the drilling teams. Clustering the two dimensional drilling sites to given number of teams were done to separate the jobs among the drilling teams. The outcome drilling site clusters total service time duration differences were minimized to a given accepted difference level by iteratively shifting jobs from the cluster, which has maximum total service time duration. This balancing was done with the minimum effect to the mean distance to the cluster centroids and avoiding oscillating between intermediate solutions ofthe iterations. The drilling site locations distance matrices were modified by adding the ‘office location’ and replacing ‘big M’ values for main diagonal distances of each outcome cluster and, sent through the Hungarian method, which is used for solving assignment problem in operational research. The outcome of the Hungarian method is the shortest path or set of sub routes. One of the distances of a respective two locations containing sub routes was replaced with ‘big M’ and rerunning through the Hungarian method was done. The graphical representations of given sub routes were taken as a guide for designing of the shortest path of each clustered drilling sites. When the number of drilling sites in a cluster is higher than ten, the given approach will become tedious, but in the geotechnical investigations industry it is not ranging higher than ten. The above mentioned algorithm of allocation of drilling teams to multiple drilling sites, were shown better optimization over the traditional practice of ‘instant team allocation for nearest location’.
