Peter Jackopeter.jacko [a] gmail.com 
Senior Lecturer (Associate Professor) in Management Science

Peter Jacko is interested in the science of efficient management of complex business processes, systems, and networks. Much of his research work benefits from the interaction of mathematics, computer science, and economics. His publications contribute to areas such as operational research, performance evaluation, stochastic modelling, queueing theory, applied probability, and machine learning. These subjects provide foundation for the modern fields of business analytics and data science. His research is motivated by realworld problems in business decisionmaking, communications networks, and healthcare management. The leading theme of his research activities is modelling and designing tractable and wellperforming strategies for efficient use of scarce resources in dynamic and stochastic environments.
His research interests are in:
His research efforts have been motivated by and the results are aimed to apply to:
See Google Scholar for the list of publications and coauthors.
Hindex: 15 (source: Google Scholar, 2021)
Erdős number: 3 (source: MathSciNet Calculator, 2021)
WARNING: The text below hasn't been updated since 2013. See the Group on Optimal Adaptive Learning (G.O.A.L.) for my current research lines.
[upon request] 
A. Asadi, P. Jacko, V. Mancuso (?): Smart TieBreaking for Scheduling with Maximum Throughput and Maximum Fairness in Cellular Networks
Status 04/2013: In preparation 
U. Ayesta, P. Jacko (2013): Method for selecting a transmission channel within a time division multiple access (TDMA) communication system,
European patent EP2384076 B1 

[paper] 
F. Cecchi, P. Jacko (2013): Scheduling of Users with Markovian TimeVarying Transmission Rates
ACM Performance Evaluation Review (to appear) (Special Issue: ACM Sigmetrics 2013) Acceptance rate: 14% (27/196) 
[slides] 
F. Cecchi*, P. Jacko (2013): Scheduling of Users with Markovian TimeVarying Transmission Rates
ACM Performance Evaluation Review (to appear) (Special Issue: ACM Sigmetrics 2013) Acceptance rate: 14% (27/196) 
[paper] 
P. Jacko, S. S. Villar (2012): Opportunistic Schedulers for Optimal Scheduling of Flows in Wireless Systems with ARQ Feedback
Proceedings of The 24th International Teletraffic Congress (ITC), pp. 18. To appear in IEEEXplore Acceptance rate: 33% 
[slides] 
P. Jacko*, S. S. Villar (2012): Opportunistic Schedulers for Optimal Scheduling of Flows in Wireless Systems with ARQ Feedback
Proceedings of The 24th International Teletraffic Congress (ITC), pp. 18. To appear in IEEEXplore Acceptance rate: 33% 
[slides] 
P. Jacko* (2011): Value of Information in Optimal FlowLevel Scheduling of Users with Markovian TimeVarying Channels
Young European Queueing Theorists Workshop V, Eindhoven, Netherlands, October 2426 invited talk Similar talks at VU Amsterdam, IMDEA Networks Madrid, FTW Vienna 
[paper] 
P. Jacko (2011): Value of Information in Optimal FlowLevel Scheduling of Users with Markovian TimeVarying Channels
Performance Evaluation 68 (11) (Special Issue: Performance 2011), pp. 10221036 Impact factor 2010: 1.168; Acceptance rate: 20% (20/99) 
[slides] 
P. Jacko* (2011): Value of Information in Optimal FlowLevel Scheduling of Users with Markovian TimeVarying Channels
Performance 2011, Amsterdam, Netherlands, October 1820 Acceptance rate: 20% (20/99) 
[paper] 
U. Ayesta, M. Erausquin, P. Jacko (2011): ResourceSharing in a Single Server with TimeVarying Capacity,
in Proceedings of FortyNinth Annual Allerton Conference on Communication, Control, and Computing, Invited paper 
U. Ayesta*, M. Erausquin, P. Jacko (2011): ResourceSharing in a Single Server with TimeVarying Capacity,
FortyNinth Annual Allerton Conference on Communication, Control, and Computing, Monticello, Illinois, USA, September 2830 Invited talk 

[slides] 
U. Ayesta, P. Jacko* (2011): NearlyOptimal Index Rules for Some Nonworkconserving Systems,
at INFORMS APS Conference, Stockholm, Sweden, July 68 in contributed session on Scheduling 
[paper] 
U. Ayesta, M. Erausquin, P. Jacko (2010): A Modeling Framework for Optimizing the FlowLevel Scheduling with TimeVarying Channels,
Performance Evaluation 67 (11) (Special Issue: Performance 2010), pp. 10141029 Impact factor 2009: 1.560; Acceptance rate: 26% (20/78) 
[slides] 
U. Ayesta, M. Erausquin, P. Jacko* (2010): A Modeling Framework for Optimizing the FlowLevel Scheduling with TimeVarying Channels,
Performance 2010, Namur, Belgium, November 1519 Acceptance rate: 26% (20/78) 
[upon request] 
U. Ayesta, P. Jacko, V. Novak (?): Scheduling Customers in a Multiclass Queue with Abandonment,
Status 04/2013: In preparation 
[paper] 
U. Ayesta, P. Jacko, V. Novak (2011): A NearlyOptimal Index Rule for Scheduling of Users with Abandonment,
in Proceedings of IEEE INFOCOM 2011 Acceptance rate: 16% (291/1823) 
[slides] 
U. Ayesta, P. Jacko, V. Novak (2011): A NearlyOptimal Index Rule for Scheduling of Users with Abandonment,
IEEE INFOCOM 2011, Shanghai, China, April 1015 Acceptance rate: 16% (291/1823) 
[slides] 
P. Jacko* (2011): Index Policies for Stochastic Dynamic Optimization,
at BCAM Colloquium at BCAM Scientific Committee Meeting, Bilbao, Spain, December 12 Invited talk 
[slides] 
P. Jacko* (2011): NearlyOptimal Solutions to Dynamic and Stochastic Resource Capacity Allocation Problems,
at INFORMS APS Conference, Stockholm, Sweden, July 68 in contributed session on Restless Bandits: Extensions and Applications 
[paper] 
P. Jacko (2011): Optimal Index Rules for Single Resource Allocation to Stochastic Dynamic Competitors,
in Proceedings of ValueTools, ACM International Conference Proceeding Series, ICST Gent Invited paper 
[slides] 
P. Jacko* (2011): Optimal Index Rules for Single Resource Allocation to Stochastic Dynamic Competitors,
Fifth International ICST Conference on Performance Evaluation Methodologies and Tools (ValueTools), Paris, France, May 1620 Invited talk 
[paper] 
P. Jacko (2010): Restless Bandits Approach to the Job Scheduling Problem and its Extensions,
in Modern Trends in Controlled Stochastic Processes, ed. A.B.Piunovskiy, Luniver Press, pp. 248267 Invited book chapter 
[abstract] [slides] 
P. Jacko* (2010): Dynamic and Stochastic Resource Capacity Allocation Problems and Adaptive Greedy Rules Based on Dynamic Prices,
Bratislava Economic Meeting, Bratislava, Slovakia, June 2426 
[Amazon] 
P. Jacko (2010): Dynamic Priority Allocation in Restless Bandit Models,
Lambert Academic Publishing, 188 pages Invited book 
[paper] 
P. Jacko (2009): Adaptive Greedy Rules for Dynamic and Stochastic Resource Capacity Allocation Problems,
Medium for Econometric Applications, 17 (4), pp. 10–16 Invited paper 
[slides] 
P. Jacko* (2009): A NearlyOptimal Solution to Stochastic and Dynamic Resource Allocation Problems,
MathPhysics Alumni Workshop, Bratislava, Slovakia, December 1618 invited talk 
[abstract] [slides] 
P. Jacko* (2009): An Optimal Index Policy for the MultiArmed Bandit Problem with ReInitializing Bandits,
Young European Queueing Theorists Workshop III, Eindhoven, Netherlands, November 1921 invited talk 
Jacko (2009) unifies into a comprehensive framework several wellknown problems in combinatorial optimization, management, stochastic scheduling, and queueing theory. The following paragraphs are dedicated to outline a couple of special cases of the stochastic and dynamic resource allocation problem known as the bandit problems.
Suppose that there are several competitors (or projects, or bandits) evolving in a stochastic manner, which simultaneously demand or service from a server that is able to serve only one competitor at time. We can decide to which competitor the server is allocated at any given moment. The competitors evolution yields certain aggregate reward, i.e., a sum of individual customer rewards that only depend on the current state of the competitor and whether it is currently being served or not. The objective is to allocate the server in such a way that the aggregate reward is maximal, either in discounted expectation or on timeaverage.
In a more general variant, we may consider a capacity of a resource divisible into a finite number of units and statedependent (discrete) capacity demands from the competitors, instead of the server able to serve strictly one competitor at time. Since this problem is PSPACEhard to solve optimally, we are typically interested in an approximate solution which is easy to implement in practice. However, for some special cases it is possible to characterize an optimal solution.
Note that the problem when the resource and the competitor demands (seen as goods and services) are continuouslydivisible is the fundamental one in neoclassical economics build up from marginalism. It should therefore not be surprising that marginal concepts also appear in the (approximate) solution to the discretelydivisible problem considered here.
Imagine a gambler in casino faced with a (fixed) number of onearmed bandit machines (or slot machines). Suppose that she is there alone and forever, and every minute she can and must choose one of the machines to play (to pull the arm). The played machine randomly evolves and yields a payoff according to its current state. The objective of the gambler is to maximize the expected discounted payoff obtained over an infinite horizon.
Imagine a physician faced with a flow of patients with a new disease. Suppose that every day she can and must choose one of the available treatments to apply to the patient coming that day. The treated patient reacts to the treatment and it is immediately known whether the treatment was successful (healing the patient) or not (dying). The objective of the physician is to heal as many patients as possible, i.e., to maximize the expected discounted number of healed patients over an infinite horizon.
The above two reallife problems lead to the same mathematical model of learning known as the multiarmed bandit problem. Its main distinguishing feature is the freezing property: the states of nonplayed machines (or nonused treatments) do not change. In fact, in the first case, the gambler is to learn which machine is the best one on average, and to exploit all the machines in favorable states during the process of learning. Similarly in the second case, the physician is to learn which treatment is the best on average, and to exploit all the other treatments in favorable states during the process of learning.
Gittins and his colleagues in the early 1970s showed that there are certain statedependent prices (now called the Gittins index values) that can be calculated for each bandit independently of the others, and such that the problem can be optimally solved by an index rule. The index rule prescribes to index (or sort) at every time period the bandits according to their prices (associated to their current states) and to play anyone of those with the highest price (colored in green in the video). The video shows evolution of the prices (or the Gittins index values) in the multiarmed bandit problem. Recall the freezing property: the prices of the nonplayed bandits do not change, since the states of such bandits do not change.
In the problem of restless bandits the freezing property is dropped. This model was introduced by Whittle (1988), where he proposed to calculate the price (sometimes called the Whittle index value) that generalizes the Gittins index value to this case. However, the Whittle index values do not necessarily exists, and further, the index rule is in general nonoptimal. Nevertheless, a growing body of literature shows that for many reallife problems the existence of such prices can be established and that the index rule performs, on average, very close to optimality.
[paper] 
K. Avrachenkov, U. Ayesta, J. Doncel, P. Jacko (2013): Congestion Control of TCP Flows in Internet Routers by Means of Index Policy
Computer Networks 57 (17), pp. 34633478 Available online at http://arxiv.org/abs/1209.3638 
[paper] 
K. Avrachenkov, U. Ayesta, J. Doncel, P. Jacko (2012): Optimal Congestion Control of TCP Flows for Internet Routers
Performance Evaluation Review 40 (3) (Special Issue: MAMA 2012), pp. 6264 
[paper] 
P. Jacko, B. Sansò (2012): Optimal Anticipative Congestion Control of Flows with TimeVarying Input Stream
Performance Evaluation 69 (2), pp. 86101 Impact factor 2010: 1.168 
[paper] 
P. Jacko, B. Sansò (2007): Congestion Avoidance with FuturePath Information,
in Proceedings of EuroFGI Workshop on IP QoS and Traffic Control, IST Press, pp. 153160 working version in Les Cahiers du GERAD, G200770, September 2007 
[slides] 
P. Jacko*, B. Sansò (2007): Congestion Avoidance with FuturePath Information,
EuroFGI Workshop on IP QoS and Traffic Control, Lisbon, Portugal, December 67 
[upon request] 
D. Graczova, P. Jacko (?): Generalized Restless Bandits and Knapsack Problem for Perishable Inventories
Status 04/2013: Minor revision 
[paper] 
P. Jacko (2013): Resource Capacity Allocation to Stochastic Dynamic Competitors: Knapsack Problem for Perishable Items and IndexKnapsack Heuristic
Annals of Operations Research, to appear, 25 pages Impact factor 2011: 0.840 
[slides] 
D. Graczova*, P. Jacko (2011): Knapsack Problem for Perishable Inventories,
Prague Economic Meeting, Prague, Czech republic, June 1618 
[slides] 
P. Jacko* (2011): Knapsack Problem for Perishable Items, IndexKnapsack Heuristic, and NearlyOptimal Revenue Management,
BCAM Workshop on Bandit Models and Applications, Bilbao, Spain, May 10 
[abstract] [slides] 
P. Jacko* (2008): Optimal Dynamic Promotion and the Knapsack Problem for Perishable Items,
VIIIth Annual Conference of INFORMS Revenue Management and Pricing Section, Montreal, Canada, June 1820 Awarded a MITACS Student Grant; among 5 out of 16 submissions; 1000 CAD 
[paper] 
P. Jacko, J. NiñoMora (2007): TimeConstrained Restless Bandits and the Knapsack Problem for Perishable Items (Extended Abstract),
Electronic Notes in Discrete Mathematics 28, pp. 145152 
[slides] 
P. Jacko*, J. NiñoMora (2006): TimeConstrained Restless Bandits and the Knapsack Problem for Perishable Items,
Sixth CzechSlovak International Symposium on Combinatorics, Graph Theory, Algorithms and Applications, Prague, Czech Republic, July 1015 
[paper] 
K. Avrachenkov, P. Jacko (2012): CCN Interest Forwarding Strategy as MultiArmed Bandit Model with Delays
Proceedings of the 6th International Conference on Network Games, Control and Optimization (NetGCoOp 2012), pages 1–6. To appear in IEEE Xplore. Full version: INRIA Research Report 7917, arXiv:1204.0416v1. 
[paper] 
P. Jacko, J. NiñoMora (2008): Marginal Productivity Index Policies for Problems of Admission Control and Routing to Parallel Queues with Delay
Universidad Carlos III de Madrid, Working paper 0872, Statistics and Econometrics Series 25 
[paper] 
P. Jacko, J. NiñoMora (2008): Admission Control and Routing to Parallel Queues with Delayed Information via Marginal Productivity Indices,
in Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools (ValueTools), ACM International Conference Proceeding Series, ICST Gent Acceptance rate: 40% (30/75) 
[slides] 
P. Jacko*, J. NiñoMora (2008): Admission Control and Routing to Parallel Queues with Delayed Information via Marginal Productivity Indices,
Third International Conference on Performance Evaluation Methodologies and Tools (ValueTools), Athens, Greece, October 2024 
[upon request] 
U. Ayesta, M. Erausquin, E. Ferreira, P. Jacko (?): Optimal Dynamic Default Risk Management with Budget Constraint
Status 04/2013: In preparation 
[draft] 
M. Larrañaga, J. Anselmi, U. Ayesta, P. Jacko, A. Romo (?): Optimization Techniques Applied to Railway Systems
Available online at http://hal.archivesouvertes.fr/hal00780524 Status 04/2013: In preparation 
[abstract] [slides] 
P. Jacko*, S. Jendroľ (2005): Some Bounds for Labeling with a Condition at Distance Two,
1st Workshop on Frequency Assignment Problems in Wireless Networks, Certosa di Pontignano (Siena), Italy, October 1415 
[paper] 
P. Jacko, S. Jendroľ (2005): Distance Coloring of the Hexagonal Lattice,
Discussiones Mathematicae Graph Theory 25 (12), pp. 151166 
[abstract] [paper SVK] 
P. Jacko (2003): Dištančné Farbenia Grafov (Distance Labelings of Graphs),
Magister Thesis, P. J. Šafárik University, Košice, Slovakia 
S. Jendroľ*, P. Jacko (2003): Distance Coloring of the Hexagonal Lattice,
10th Workshop on Graph Theory  Colourings, Independence and Domination, Karpacz, Poland, September 2226 

[abstract] 
P. Jacko, A. Marcinová* (2002): The Distance Colouring of Regular Tilings of the Plane,
Graphs 2002, Rejvíz, Czech Republic, May 2731 
[paper SVK] [pictures] 
P. Jacko (2001): Dištančné Chromatické Číslo Šesťuholníkovej Siete (Distance Chromatic Number of Hexagonal Lattice),
Students' Research Conference, P. J. Šafárik University, Košice, Slovakia 
[paper]  P. Jacko (preprint 2005): Decisions by Inexperienced Agents 
[paper] 
P. Jacko (2004): Incentive Alignment in Corporation,
in Proceedings of Teoretické aspekty prierezových ekonomík II, Košice, Slovakia, October 22 
Last modified: 11/2018