Endüstri Mühendisliği Bölümü Yayın Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/279

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Citation Count: Karasakal, Orhan; Karasakal, Esra; Silav, Ahmet (2021). "A multi-objective approach for dynamic missile allocation using artificial neural networks for time sensitive decisions", Soft Computing, Vol. 25, No. 15, pp. 10153-10166.
A multi-objective approach for dynamic missile allocation using artificial neural networks for time sensitive decisions
(2021) Karasakal, Orhan; Karasakal, Esra; Silav, Ahmet; 216553
In this study, we develop a new solution approach for the dynamic missile allocation problem of a naval task group (TG). The approach considers the rescheduling of the surface-to-air missiles (SAMs), where a set of them have already been scheduled to a set of attacking anti-ship missiles (ASMs). The initial schedule is mostly inexecutable due to disruptions such as neutralization of a target ASM, detecting a new ASM, and breakdown of a SAM system. To handle the dynamic disruptions while keeping efficiency high, we use a bi-objective model that considers the efficiency of SAM systems and the stability of the schedule simultaneously. The rescheduling decision is time-sensitive, and the amount of information to be processed is enormous. Thus, we propose a novel approach that supplements the decision-maker (DM) in choosing a Pareto optimal solution considering two conflicting objectives. The proposed approach uses an artificial neural network (ANN) that includes an adaptive learning algorithm to structure the DM's prior articulated preferences. ANN acts like a DM during the engagement process and chooses one of the non-dominated solutions in each rescheduling time point. We assume that the DM's utility function is consistent with a non-decreasing quasi-concave function, and the cone domination principle is incorporated into the solution procedure. An extensive computational study is provided to present the effectiveness of the proposed approach.
Citation Count: Karasakal, O., Özdemirel, N.E., Kandiller, L. (2011). Anti-ship missile defense for a naval task group. Naval Research Logistics, 58(3), 305-322. http://dx.doi.org/10.1002/nav.20457
Anti-ship missile defense for a naval task group
(Wiley-Blackwell, 2011) Karasakal, Orhan; Özdemirel, Nur Evin; Kandiller, Levent; 2634; 5706
In this study, we present a new formulation for the air defense problem of warships in a naval task group and propose a solution method. We define the missile allocation problem (MAP) as the optimal allocation of a set of surface-to-air missiles (SAMs) of a naval task group to a set of attacking air targets. MAP is a new treatment of an emerging problem fostered by the rapid increase in the capabilities of anti-ship missiles (ASMs), the different levels of air defense capabilities of the warships against the ASM threat, and new technology that enables a fully coordinated and collective defense. In addition to allocating SAMs to ASMs, MAP also schedules launching of SAM rounds according to shoot-look-shoot engagement policy or its variations, considering multiple SAM systems and ASM types. MAP can be used for air defense planning under a given scenario. As thorough scenario analysis would require repetitive use of MAP, we propose efficient heuristic procedures for solving the problem
Citation Count: Silav, Ahmet; Karasakal, Esra; Karasakal, Orhan (2021). "Bi-objective dynamic weapon-target assignment problem with stability measure", Annals of Operations Research.
Bi-objective dynamic weapon-target assignment problem with stability measure
(2021) Silav, Ahmet; Karasakal, Esra; Karasakal, Orhan; 216553
In this paper, we develop a new bi-objective model for dynamic weapon-target assignment problem. We consider that the initial weapon assignment plan of defense is disrupted during engagement because of a destroyed air target, breakdown of a weapon system or a new incoming air target. The objective functions are defined as the maximization of probability of no-leaker and the maximization of stability in engagement order of weapon systems. Stability is defined as assigning same air target in sequence in engagement order of a weapon system so that reacquisition and re-tracking of air target are not required by sensors. We propose a new solution procedure to generate updated assignment plans by maximizing efficiency of defense while maximizing stability through swapping weapon engagement orders. The proposed solution procedure generates non-dominated solutions from which defense can quickly choose the most-favored course of action. We solve a set of representative problems with different sizes and present computational results to evaluate effectiveness of the proposed approach.
Citation Count: Silav, Ahmet; Karasakal, Orhan; Karasakal, Esra, "Bi-objective missile rescheduling for a naval task group with dynamic disruptions", Naval Research Logisics, Vol. 66, No. 7, pp. 596-615, (2019).
Bi-objective missile rescheduling for a naval task group with dynamic disruptions
(Wiley, 2019) Sılav, Ahmet; Karasakal, Orhan; Karasakal, Esra; 216553
This paper considers the rescheduling of surface-to-air missiles (SAMs) for a naval task group (TG), where a set of SAMs have already been scheduled to intercept a set of anti-ship missiles (ASMs). In missile defense, the initial engagement schedule is developed according to the initial state of the defensive and attacking units. However, unforeseen events may arise during the engagement, creating a dynamic environment to be handled, and making the initial schedule infeasible or inefficient. In this study, the initial engagement schedule of a TG is assumed to be disrupted by the occurrence of a destroyed ASM, the breakdown of a SAM system, or an incoming new target ASM. To produce an updated schedule, a new biobjective mathematical model is formulated that maximizes the no-leaker probability value for the TG and minimizes the total deviation from the initial schedule. With the problem shown to be NP-hard, some special cases are presented that can be solved in polynomial time. We solve small size problems by the augmented epsilon-constraint method and propose heuristic procedures to generate a set of nondominated solutions for larger problems. The results are presented for different size problems and the total effectiveness of the model is evaluated.

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