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introduction to agent and a MAS, and discusses MAS interaction and communication, and the application of a MAS in scheduling.
2.5.1 Motivations to Use MAS
The critique of current approaches Section 2.3.4 explains that most of the current approaches in bus crew scheduling are concentrated on achieving optimum schedules,
and they succeed in finding an optimum or near-optimum schedule Wren, 2004. However, very little research considers minimising the effect of UE problems on crew
schedules such as Huisman and Wagelman, 2006; Wren et al., 2003. Based on the practical experiences of bus companies as discussed in Section 2.4.3: Interview
Analysis, UE problems caused by traffics, crews or vehicles are likely to take place every day and every time. There is no absolute solution, and the supervisor has to
manage the problem case-by-case. A supervisor has great responsibilities to make sure buses operate on schedules, to
manage resources and to deal with UE problems. In the occurrence of UE, a supervisor must perform appropriate adjustments to the schedule or change resource allocation.
Crew rescheduling is a way of dealing with such events, which is currently done manually. As mentioned in the critique of current approaches and confirmed by the
findings from the interviews, existing crew scheduling systems only provide optimum schedules and do not support the process of real-time crew rescheduling. Manually
tackling such problems is usually hard and making decisions is slow, prone to error and not optimum. These limitations necessitate the need for an automated system that
supports the process of crew rescheduling to assist supervisors in dealing with UE problems that affect crew schedules.
There are two important characteristics in crew rescheduling that should be borne in mind before selecting a tool to implement the proposed solution. The characteristics are
the nature of the UE problem and the desired solution. The nature of UE problems are uncertain and not uniform no one knows whatwhen will happen and how it will
happen. The solution desired is as quick as possible within seconds or minutes. The capability to react in an uncertain environment whilst at the same time providing quick
solutions in real time are essential for automated crew rescheduling systems. The
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selected tool should be able to fulfil these requirements in order to achieve the aim of the proposed system.
Current approaches such as heuristics, mathematical and others have some limitations as discussed in the critiques of current approaches. Heuristics approaches are not easily
adaptable, and they were not suitable for general optimisation Wren and Rouseau, 1995; Wren, 1998. Mathematical approaches are usually slow to produce results
because they are computationally intensive when it comes to complex situations Kwan et al., 1999. Other approaches genetic algorithm, tabu search, ant system, and
constraint programming were not reported to have capabilities in operating in uncertain environments. These limitations as mentioned above prevented us from adopting such
approaches for the proposed system. Alternatively, a MAS can fulfil the requirements mentioned above and be capable of
reacting in uncertain environments and providing quick solutions in real time Jennings et al., 1998; Ferber, 1999; Wooldridge, 2002. A MAS has been used for other
scheduling fields meeting scheduling, manufacturing scheduling, events scheduling and etc. where similar problem are faced i.e. uncertain environment. The following
subsections explain details of a MAS theoretical description and the use of a MAS in scheduling.
2.5.2 Introduction to Agent and MAS
