SimRisk: An Integrated Open-Source Tool for Agent-Based ...

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Q1/2010 Q2/2010 Q3/2010 Q4/2010 Q1/2011 Q2/2011 Q3/2011 Q4/2011 Q1/2012 Q2/2012 Q3/2012 Q4/2012 Agent-based Stochastic Modeling Extension of Markov Decision Processes Component-based design Model reusability Support for decision optimization Re-targetable generative simulation engine Load balance based on structure information Thread-scheduling optimization Formal stochastic analysis Pattern-based problem formulation Proof extract and game-based interpretation Open source tools development Table 1: The project timeline. 5.5 Project timeline Table 1 gives the project timeline. The project will be carried out in a three-year period with efforts of two faculty members, one Ph.D. student, and one Masters student. Table 1 lists durations and finish time of activities defined for each specific aim. 5.6 Project management In this project Li Tan will lead efforts on developing high-performance reconfigurable simulation technology, automated formal stochastic analysis technique, and the open-source tool Simrisk. Shenghan Xu will lead efforts on agent-based stochastic modeling and the empirical study of new technologies developed in this project. The University of Idaho and Washington State University Pullman campus are connected by a 7-mile highway. During the course of this project we will hold weekly research meeting between two groups. 6 Broader impact Stochastic analysis of supply chains is important for a wide range of applications, including risk supply-chain risk analysis[Chen and Zhang, 2008], contracting [van Delft and Vial, 2004], and performance evaluation [Wei et al., 2007]. We expect that the success of this project will advance research on these application. Because of the practical significance of stochastic analysis in supply-chain management, the project is also expected to assist companies who are interested in streamlining their supply chains. In addition, we plan to promote knowledge dissemination and technology transfer by publications, the distribution of an open-source tool, and educational programs. Theories and methods developed in this project will be shared in research community 14
via publications in leading journals and major conferences in operations management and computer science. The open-source tool will be free available for practitioners who want to try out new technologies and incorporate them to their existing workflow. Built on the leading software development framework Eclipse, the tool will also provide an open framework for researchers and engineers who want to contribute and/or integrate new stochastic analysis technologies. Part of grant will be used to support a women faculty member (Shenghan Xu) for her interdisciplinary in operations management and computer science. A significant amount of the grant will be used to support a Ph.D student and a M.S. student. They will work with PIs to develop underlying technologies. Part of this research will be built into the current and future courses on supply-chain management, mathematical modeling, software engineering, and parallel computing in Washington State University and the University of Idaho. Li Tan also leads a very active undergraduate research program on software engineering in WSU, in which students help design and develop a variety of research tools, including a preliminary implementation of Simrisk as the proof of concepts. Through the development of these research tools, undergraduate students gained value experience in software design, and they learnt skills essential to interdisciplinary study. If funded, this project will contain a significant amount of undergraduate research activities. A group of undergraduate students will work with PIs and graduate students on the design and the implementation of Simrisk. The Simrisk toolkit developed in this research will be also used in an upper-division undergraduate class in supply-chain management in the University of Idaho. Its agent-based visual model editing environment will help students develop intuition behind supply-chain risk management. The tool will also allow students to try “what-if” scenarios for different risk management strategies and learn how to optimize supply chains by balancing various factors. 15
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