| Summary: | 碩士 === 國立臺東大學 === 資訊管理學系碩士班 === 97 === The information security and the system quality for the banking are
extremely important. However, the financial IT industry in order to save
the cost of training technical personnel expenditures, system outsourcing
has been a trend. On present situation, bank IT has to establish a good
consultative process and manage the project efficiently to have the
opportunity to create the win-win situation. In the beginning of project, the
plan proposed to be done must be drafted in consultation with the
participants, so that the participants are willing to move forward toward
common goals. When the project plan had been established, systems
development also needs management. This is the project management duty
for processing and coordination of emergency situation. Whether plan is
beginning or proceeding, "project management" is an important issue.
Therefore, it makes PM more important and necessary.
However, project managers are not omnipotent in reality. On the
premise of application and practicality, resources and suggestion provided
by experts to solve the problem is project managers’ responsibilities, yet in
progress of Project Management. In reality, it needs a lot of management
attribute, such as manpower, cost, category, time and so on. These factors
often change with environment. Our research established an Automated
Negotiation Mechanism that progresses similar to human thinking process
in project management on the basis of Multi-agent systems. In this study,
we also build the system model to verify the feasibility of our consultation
mechanism and genetic algorithm, and show the results of agent
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consulation simulation and the best special case combination suggested by
the genetic algorithm when the negotiations fail.
※This study provides two core concepts:
1. When agent consultative mechanism endows agents with different
negotiation behavior and tasks of PM, the automated negotiation
system has become more user-friendly.
2. If the consultation fails, there will be a genetic algorithm trying to find
the best combination.
The purpose is to apply the agent in an integrated consultative
mechanism, so that participants can consider their own interests in
accordance with the properties to make adjustments flexible. For example,
in the consultation, IT will adopt the most stringent requirements of system
quality. In this regard, IT is impossible to make concessions. If all
proposals cannot meet the participants’ needs, the genetic algorithm will be
carried out to find the best combination according to the cost-effective
value. Consequently, the best combination is used to offer participants
further choice.
In this research mentioned when consultation defeats, the system will
try to find the best combination to give advice on the proposal, and to
supply a record of the results to the agent system. By this way will
accumulate and train thinking and decision-making capacity gradually, the
model in the current research less mentioned. In the future may supply
direction of the following research.
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