Author Archives: benkoczi

Optimization Seminar Series – Friday May 21, 2021 @ 11 am MDT

Speaker: Oluwaseun (Francis) Lijoka
Date: May 21, 2021 (Friday)
Time: 11:00 AM

Join Zoom Meeting

Meeting ID: 957 6929 8984
Passcode: 985604

Title: Capacity Provisioning on Dynamic Path Network
Abstract: The aim of the talk is to introduce the problem of allocating capacities to edges of a dynamic path network with n vertices, in such a way that the evacuation completion time towards a single sink node (minmax criterion) is minimized. Our algorithm determines the optimal assignment of capacities to all edges of the network from a given total budget under the assumption that the location of the sink is known. In perspective with other evacuation and sink location problems, our model is suitable for planning the evacuation of remote and sparsely populated areas. Uncovered properties and vital data structures will be discussed.

Everyone is welcome.

Bio: Francis is a PhD student in the Optimization Research Group in our department. We all know Francis, don’t we?

Optimization Seminar Series – Thr May 30, 2019 @ 1pm in C630

Speaker: Dr. Vijay Mago
Title: Social science to artificial intelligence and beyond – a journey
Room: C630
Date: Thr, May 30, 2019
Time: 1:00 pm – 1:50 pm

Abstract: As researchers in computer science, we always face a challenge when people ask about the application of our research; policy makers talk about how computer science can help them predict the impact of policies - knowledge translation for practitioners, and as theoretical scientists, we want to improve the existing algorithm or develop new ones - incremental research. The focus of this talk is to present the recent works at DataLAB at the Lakehead University, where we have applied our research outcomes to – a) support the student mobility between colleges and universities, b) develop law cases repository c) understand the contributory factors of success for transfer students, d) build artificial intelligent facilitator for conceptual map building, e) present a simulation framework to test the policies for homeless in Montreal, f) design a new algorithm for semantic analysis, g) design an improved algorithm to automate essay evaluation, and finally h) a mechanism to host big data on High Performance computing for near real-time searching and querying.

Biography: Vijay Mago received the Ph.D. degree in computer science from Panjab University, India, in 2010. In 2011, he joined the Modelling of Complex Social Systems Program at the IRMACS Centre of Simon Fraser University. He is currently an Associate Professor with the Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada, where he teaches and conducts research in areas, including big data analytics, machine learning, natural language processing, artificial intelligence, medical decision making, and Bayesian intelligence. He has served on the program committees of many international conferences and workshops. In 2017, he joined Technical Investment Strategy Advisory Committee Meeting for Compute Ontario. He has published extensively (more than 50 peer reviewed articles) on new methodologies based on soft computing and artificial intelligence techniques to tackle complex systemic problems, such as homelessness, obesity, and crime. He currently serves as an Associate Editor for IEEE Access and BMC Medical Informatics and Decision Making and as a Co-Editor for the Journal of Intelligent Systems.


  • Selfish mining: Dr. Muhammad Khan’s presentation for BTS 2018.
  • Blockchain based systems and IoT: one graduate student supervised

Lethbridge Blockchain Workshop and Hackathon

The Lethbridge Blockchain Workshop and Hackathon is a problem pitch contest and smart contract coding competition, organized at the University of Lethbridge, Alberta, Canada by members of the Optimization Research Group in collaboration with colleagues from the Dhillon School of Business and with the support of the University-Industry Liaison Office.

Organizers: Robert Benkoczi (ORG), Muhammad Khan (ORG), Afrooz Maotari-Kazerouni (DSB), Greg Vilk (UILO), Rossitsa Yalamova (DSB).

Additional information

Optimization Seminar Series – Wed Oct 17, 2018 @ noon in C630

Speaker: Dr Fatih Celik.
Title: Behavior of honeybees foraging for nectar and a large scale routing protocol implementation in wireless sensor networks
Room: C630
Date: Wed, Oct 17, 2018
Time: 12:00 – 12:50 pm.

Insect colonies are an attractive research topic for the researcher in electrical engineering and computer science who develops and designs shortest path algorithms. Bees use energy very efficiently and have the ability to find shortest routes to their source of food. Wireless sensor networks have similarities with honeybee colonies in terms of finding shortest paths for communication and consuming energy efficiently. In this presentation, we focus on an optimal method based on swarm intelligence (SI) inspired by honeybees and the behavior of honeybee foraging for nectar. Also, we analyze a routing protocol implementation in wireless sensor networks.

Fatih Celik received his Ph.D. in Electronics and Computer Science from the University of Sakarya, Turkey. He was an Assistant Professor at Sakarya University and a visiting scholar at University of Pittsburgh, USA. His research interests include parallel and distributed simulation, modeling and simulation of large-scale networks, biologically-inspired optimization schemes, cognitive radio networks, mobile ad hoc networks and wireless sensor networks. His main research interest lies in parallel and distributed simulation and routing protocols for the wireless sensor network.

CPSC 4110/5110/7110 – Introduction to Algorithms in Facility Location

The course materials are available on moodle to registered students.
Course outline.
There is no textbook for this course. Readings from academic articles will be available on the moodle page of the course. A list of classical papers in facility location is available from Trevor Hale’s bibliography.

CPSC 4210/5210: Wireless Networks

The course is available on Moodle.

Optimization Seminar Series – Fri Dec 16, 2016, noon, in B543

Title: Parameterized Query Complexity of Quantum Computation
Speaker: Parijat Purohit, MSc candidate, Optimization Research Group

Abstract: Our proposal is to analyze the query complexity of a problem as a function of some parameter. This extends the parameterized complexity studies in the classical setting. We illustrate the applicability of this methodology on two seemingly unrelated problems. We parameterize the degree of imbalance for an arbitrary function whether it is balanced or not. We consider the same parameterization for the self-duality of a function.
Joint work with Saurya Das (Physics), Daya Gaur, Shahadat Hossain, and Robert Benkoczi.
Work accepted for presentation as a poster at the 20th Annual Conference on Quantum Information Processing, Seattle, WA.

Optimization Seminar Series – Wed. Oct 19, 2016, noon, in C620

Title: Algorithms for Barrier Coverage with Wireless Sensors
Speaker: Dr. Xiao Zhang, City University of Hong-Kong

Abstract: Barrier coverage is a critical problem in wireless sensor networks. In the area, we study the barrier coverage problem from two perspectives, i.e., static sensors with adjustable sensing ranges and mobile sensors with fixed sensing ranges. Specifically, in the first topic, we consider the barrier coverage problem for a line interval, in which we are given a set of sensors and the goal is to determine a range assignment with the lowest possible cost. In the second topic, we consider the problem of covering a line interval by mobile sensors such that the maximum of moving cost is minimized.

Bio: Xiao Zhang received his PhD degree from Department of Computer Science in City University of Hong Kong, Hong Kong, 2016. He was a visiting scholar with the Department of Computer Science in Utah State University, Logan, Utah, USA, in 2015. His research interests include algorithms design and analysis, wireless sensor networks.

CPSC 3780 for Dr. Gaur (Sept 20-22, 2016)

Topics: Fourier transforms, the sampling theorem, Shannon formula for the capacity of a communication channel.