A Multi-Agent Task Scheduling In University Environment

Tariq Mahmood, M. Shahid Farid

Abstract


Task scheduling problems are involved in almost every field of life from industry, where scheduling of employees on different machines with different shifts with respect to various constraints, to universities where scheduling involved in time tabling of classes and faculty, in examination scheduling, laboratory scheduling, staff scheduling and so on. Scheduling problem involves scheduling of different resources under various constraints to attain optimal results. In this paper we present a multi-agent based solution to Task Scheduling Problem (TSP) in university environment. It involves two main scheduling  problmes; first, time tabling probelm (TTP) and second  examination scheduling problem (ESP). In time tabling problem, a time table of classes is consturcted subject to different constraints; like rooms, subjects, teachers, degrees and semester with in a degree program. in examination scheduling problem is central to scheduling issue to every university. In ESP, the schedule of the examination of different courses of different degrees invigilated by different faculty members each with his/her availability constraints, is carried out. The problem is even worse when students of different degrees takes a shared course and when there are add-drops students in a course. In this case, the complexity of the scheduling problem doubles, now scheduling has to done with respect to the constraints of faculty, degree and also to  decrease the number of clashes in examination. An agent based solution to TSP is proposed in this paper which is also implemented and tested over different scenarios and optimal results are achieved in negligible amount of time.

DOI: http://dx.doi.org/10.11591/ij-ai.v1i4.708


Keywords


Task Scheduling, Examination Scheduling Problem, approximation algorithms

Full Text:

PDF

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

View IJAI Stats