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Mohammad Amini, Abstract: |
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needs, simultaneously. This problem, called the Constraint
Satisfiability Problem (CSP),arises
in a large number of real-world settings. Important examples include
the "Triad of Detailing" and its interconnected allocation,
placement, and assignment or detailing functions within the Navy, as
well as related applications other military organizations. In addition, a large number of other decision problems can be reframed as
CSPs. These problems are known to be NP-complete, implying their computational intractability if optimal solutions are required. Hence, success of current methods that seek the "best" solution is limited to "small-scale"
CSPs. For some large-scale problem instances, current methods are often unable even to find feasible solutions. The objectives of this proposed research are as follows. (1) Investigate new approaches to modeling CSP problems in the form of a network optimization problem, using special representations referred to as NETFORMS. (2) Develop and implement new and effective generalized network based branch-and-bound approaches to the NETFORM models. The solution generation process will take advantage of the best existing generalized network solution approaches that have been established to be two orders of magnitude faster in obtaining optimal solutions than alternative approaches. The new approach will allow decision-makers, within military or civilian organizations, to approach real-world, "large-scale" CSP instances more effectively. A major by product of this research will be the creation of a general solution platform for solving a large variety of combinatorial problems that have been recast into the NETFORM framework. |
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