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7.3 Conclusions
The main findings and conclusions derived from this research are reported below: • MAS can be used as a tool to model and implement the automated crew
rescheduling system. In this research MAS was proposed as a tool to implement the automated crew rescheduling system because MAS can provide a quick
solution in real-time and in uncertain environments. Thereafter the research proposed CRSMAS that use the concept of MAS. In the CRSMAS architecture
there are two types of agents that are the duty agent DA and the crew agent CA. CA represents a crew, and DA corresponds to a duty that needs to find a
crew. The agents perform the rescheduling process through negotiation between them. Based on the experiments it can be concluded that MAS is suitable for
automating the crew rescheduling process and is capable of quick rescheduling, whether facing single or multiple events at the same time.
• MAS has limitations in dealing with different event at the same time. From the Multiple Events experiment it was found that MAS cannot simulate different
types of event at the same time. The limitation is because in different events there are different rules. In Virtual World, agents only can negotiate with one set
of rules at a time. • Successful rescheduling is not only dependant on the tool. Findings from the
Single Event experiment show that the success of rescheduling is not only dependant on the tool, but also on other factors such as the characteristics of
crew schedules and the period of UE. The factors of crew schedules’ characteristics are the number of duties, duty spreading, duty distribution and
the period of relief time. The longer the period of UE, the less chance there is of rescheduling success.
• MAS is capable of quick rescheduling. From the empirical evidence Single and Multiple Events experiments MAS is capable of performing quick rescheduling
in real-time. The rescheduling speed is measured as the time taken to perform
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the rescheduling process. Based on the results, the average time taken for Single Event is 1.59 seconds and for Multiple Events is 1.31 seconds. However, the
average for Single Event is higher than for Multiple Event. One of the reasons for this is that in Single Event there is more than one round of rescheduling and
therefore it takes more time. This average time is considered quick for the real- time environment. The analysis also shows that that the speed is dependent on
the size of schedules; the larger a schedule is, the longer it takes to perform rescheduling. The reason for this is that all the agents have to negotiate with
each other and as a result it takes time when the number of agents crewsduties is large.
7.4 Summaries of Contributions