Kyle Lin - Academia.edu (original) (raw)
Papers by Kyle Lin
arXiv (Cornell University), May 17, 2023
arXiv (Cornell University), Jun 19, 2023
arXiv (Cornell University), Oct 15, 2017
arXiv (Cornell University), Aug 14, 2019
Naval Research Logistics, Oct 21, 2014
Operations Research, Jan 7, 2020
Operations Research, Sep 1, 2022
A defender dispatches patrollers to circumambulate a perimeter to guard against potential attacks... more A defender dispatches patrollers to circumambulate a perimeter to guard against potential attacks. The defender decides on the time points to dispatch patrollers and each patroller’s direction and speed, as long as the long-run rate at which patrollers are dispatched is capped at some constant. An attack at any point on the perimeter requires the same amount of time, during which it will be detected by each passing patroller independently with the same probability. The defender wants to maximize the probability of detecting an attack before it completes, while the attacker wants to minimize it. We study two scenarios, depending on whether the patrollers are undercover or wear a uniform. Conventional wisdom would suggest that the attacker gains advantage if he can see the patrollers going by so as to time his attack, but we show that the defender can achieve the same optimal detection probability by carefully spreading out the patrollers probabilistically against a learning attacker.
European Journal of Operational Research, Jun 1, 2008
Probability in the Engineering and Informational Sciences, Oct 1, 2001
arXiv (Cornell University), May 6, 2019
IFAC Proceedings Volumes, 2006
Wiley Encyclopedia of Operations Research and Management Science, Feb 15, 2011
... KYLE Y. LIN Operations Research Department, Naval Postgraduate School, Monterey, California .... more ... KYLE Y. LIN Operations Research Department, Naval Postgraduate School, Monterey, California ... 1). One such strategy is to instruct the gambler to wage 1onthefirstbetandtodoubleupthewageraftereachloss,inthehopethathewilleventuallywinabetsoastowin1 on the first bet and to double up the wager after each loss, in the hope that he will eventually win a bet so as to win 1onthefirstbetandtodoubleupthewageraftereachloss,inthehopethathewilleventuallywinabetsoastowin1 ...
Journal of Applied Probability, Jun 1, 2004
This paper presents a single-server loss queueing system where customers arrive according to a Po... more This paper presents a single-server loss queueing system where customers arrive according to a Poisson process. Upon arrival, the customer presents itself to a gatekeeper who has to decide whether to admit the customer into the system without knowing the busy–idle status of the server. There is a cost if the gatekeeper blocks a customer, and a larger cost if an admitted customer finds the server busy and therefore has to leave the system. The goal of the gatekeeper is to minimize the total expected discounted cost on an infinite time horizon. In the case of an exponential service distribution, we show that a threshold-type policy—block for a time period following each admission and then admit the next customer—is optimal. For general service distributions, we show that a threshold-type policy need not be optimal; we then present a sufficient condition for the existence of an optimal threshold-type policy.
Operations Research, Apr 1, 2007
European Journal of Operational Research, Sep 1, 2009
This paper presents a single-server loss queueing system where customers arrive according to a Po... more This paper presents a single-server loss queueing system where customers arrive according to a Poisson process. Upon arrival, the customer presents itself to a gatekeeper who has to decide whether to admit the customer into the system without knowing the busy-idle status of the server. There is a cost if the gatekeeper blocks a customer, and a larger cost if an admitted customer finds the server busy and therefore has to leave the system. The goal of the gatekeeper is to minimize the total expected discounted cost on an infinite time horizon. In the case of an exponential service distribution, we show that a threshold-type policy-block for a time period following each admission and then admit the next customer-is optimal. For general service distributions, we show that a threshold-type policy need not be optimal; we then present a sufficient condition for the existence of an optimal threshold-type policy.
International Journal of Operational Research, 2017
arXiv (Cornell University), May 17, 2023
arXiv (Cornell University), Jun 19, 2023
arXiv (Cornell University), Oct 15, 2017
arXiv (Cornell University), Aug 14, 2019
Naval Research Logistics, Oct 21, 2014
Operations Research, Jan 7, 2020
Operations Research, Sep 1, 2022
A defender dispatches patrollers to circumambulate a perimeter to guard against potential attacks... more A defender dispatches patrollers to circumambulate a perimeter to guard against potential attacks. The defender decides on the time points to dispatch patrollers and each patroller’s direction and speed, as long as the long-run rate at which patrollers are dispatched is capped at some constant. An attack at any point on the perimeter requires the same amount of time, during which it will be detected by each passing patroller independently with the same probability. The defender wants to maximize the probability of detecting an attack before it completes, while the attacker wants to minimize it. We study two scenarios, depending on whether the patrollers are undercover or wear a uniform. Conventional wisdom would suggest that the attacker gains advantage if he can see the patrollers going by so as to time his attack, but we show that the defender can achieve the same optimal detection probability by carefully spreading out the patrollers probabilistically against a learning attacker.
European Journal of Operational Research, Jun 1, 2008
Probability in the Engineering and Informational Sciences, Oct 1, 2001
arXiv (Cornell University), May 6, 2019
IFAC Proceedings Volumes, 2006
Wiley Encyclopedia of Operations Research and Management Science, Feb 15, 2011
... KYLE Y. LIN Operations Research Department, Naval Postgraduate School, Monterey, California .... more ... KYLE Y. LIN Operations Research Department, Naval Postgraduate School, Monterey, California ... 1). One such strategy is to instruct the gambler to wage 1onthefirstbetandtodoubleupthewageraftereachloss,inthehopethathewilleventuallywinabetsoastowin1 on the first bet and to double up the wager after each loss, in the hope that he will eventually win a bet so as to win 1onthefirstbetandtodoubleupthewageraftereachloss,inthehopethathewilleventuallywinabetsoastowin1 ...
Journal of Applied Probability, Jun 1, 2004
This paper presents a single-server loss queueing system where customers arrive according to a Po... more This paper presents a single-server loss queueing system where customers arrive according to a Poisson process. Upon arrival, the customer presents itself to a gatekeeper who has to decide whether to admit the customer into the system without knowing the busy–idle status of the server. There is a cost if the gatekeeper blocks a customer, and a larger cost if an admitted customer finds the server busy and therefore has to leave the system. The goal of the gatekeeper is to minimize the total expected discounted cost on an infinite time horizon. In the case of an exponential service distribution, we show that a threshold-type policy—block for a time period following each admission and then admit the next customer—is optimal. For general service distributions, we show that a threshold-type policy need not be optimal; we then present a sufficient condition for the existence of an optimal threshold-type policy.
Operations Research, Apr 1, 2007
European Journal of Operational Research, Sep 1, 2009
This paper presents a single-server loss queueing system where customers arrive according to a Po... more This paper presents a single-server loss queueing system where customers arrive according to a Poisson process. Upon arrival, the customer presents itself to a gatekeeper who has to decide whether to admit the customer into the system without knowing the busy-idle status of the server. There is a cost if the gatekeeper blocks a customer, and a larger cost if an admitted customer finds the server busy and therefore has to leave the system. The goal of the gatekeeper is to minimize the total expected discounted cost on an infinite time horizon. In the case of an exponential service distribution, we show that a threshold-type policy-block for a time period following each admission and then admit the next customer-is optimal. For general service distributions, we show that a threshold-type policy need not be optimal; we then present a sufficient condition for the existence of an optimal threshold-type policy.
International Journal of Operational Research, 2017