Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a problem in which a service vehicle seeks to defend a deadline (boundary) from dynamically arriving mobile targets. The environment is a rectangle and the deadline is one of its edges. Targets arrive continuously over time on the edge opposite the deadline, and move towards the deadline at a fixed speed. The goal for the vehicle is to maximize the fraction of targets that are captured before reaching the deadline.  consider two cases; when the service vehicle is faster than the targets, and; when the service vehicle is slor than the targets. In the first case  develop a novel vehicle policy based on computing longest paths in a directed acyclic graph.  give a lor bound on the capture fraction of the policy and show that the policy is optimal when the distance beten the target arrival edge and deadline becomes very large.  present numerical results which suggest near optimal performance away from this limiting regime. In the second case, when the targets are slor than the vehicle,  propose a policy based on servicing fractions of the translational minimum Hamiltonian path. In the limit of low target speed and high arrival rate, the capture fraction of this policy is within a small constant factor of the optimal.
['Stephen L. Smith', 'Shaunak D. Bopardikar', 'Francesco Bullo']
I am writing a research paper on a idea A dynamic boundary guarding problem with translating targets
[{"from": "human", "value": "I am writing a research paper on a idea A dynamic boundary guarding problem with translating targets"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  introduce a problem in which a service vehicle seeks to defend a deadline (boundary) from dynamically arriving mobile targets. The environment is a rectangle and the deadline is one of its edges. Targets arrive continuously over time on the edge opposite the deadline, and move towards the deadline at a fixed speed. The goal for the vehicle is to maximize the fraction of targets that are captured before reaching the deadline.  consider two cases; when the service vehicle is faster than the targets, and; when the service vehicle is slor than the targets. In the first case  develop a novel vehicle policy based on computing longest paths in a directed acyclic graph.  give a lor bound on the capture fraction of the policy and show that the policy is optimal when the distance beten the target arrival edge and deadline becomes very large.  present numerical results which suggest near optimal performance away from this limiting regime. In the second case, when the targets are slor than the vehicle,  propose a policy based on servicing fractions of the translational minimum Hamiltonian path. In the limit of low target speed and high arrival rate, the capture fraction of this policy is within a small constant factor of the optimal."}]