Mateja Đumić

 

PhD student
Department of Mathematics
Josip Juraj Strossmayer University of Osijek
Trg Ljudevita Gaja 6
Osijek, HR-31000, Croatia¸
phone: +385-31-224-805
fax: +385-31-224-801
email:  mdjumic @ mathos.hr
office:  7 (ground floor)

 


Research Interests

Genetic algorithms
Genetic programming
Resource constrained project scheduling problem


Degrees

MSc in Mathematics, Department of Mathematics, University of Osijek,Croatia, 2014.
BSc in Mathematics, Department of Mathematics, University of Osijek, Croatia, 2011.

 

Publications

Journal Publications

  1. M. Đumić, D. Šišejković, R. Čorić, D. Jakobović, Evolving priority rules for resource constrained project scheduling problem with genetic programming, Future Generation Computer Systems 86 (2018), 211-221
    The main task of scheduling is the allocation of limited resources to activities over time periods to optimize one or several criteria. The scheduling algorithms are devised mainly by the experts in the appropriate fields and evaluated over synthetic benchmarks or real-life problem instances. Since many variants of the same scheduling problem may appear in practice, and there are many scheduling algorithms to choose from, the task of designing or selecting an appropriate scheduling algorithm is far from trivial. Recently, hyper-heuristic approaches have been proven useful in many scheduling domains, where machine learning is applied to develop a customized scheduling method. This paper is concerned with the resource constrained project scheduling problem (RCPSP) and the development of scheduling heuristics based on Genetic programming (GP). The results show that this approach is a viable option when there is a need for a customized scheduling method in a dynamic environment, allowing the automated development of a suitable scheduling heuristic.
  2. N. Čerkez, R. Čorić, M. Đumić, D. Matijević, Finding an optimal seating arrangement for employees traveling to an event, Croatian Operational Research Review 6/2 (2015), 419-427
    The paper deals with modelling a specific problem called the Optimal Seating Arrangement (OSA) as an Integer Linear Program and demonstrated that the problem can be efficiently solved by combining branch-and-bound and cutting plane methods. OSA refers to a specific scenario that could possibly happen in a corporative environment, i.e. when a company endeavors to minimize travel costs when employees travel to an organized event. Each employee is free to choose the time to travel to and from an event and it depends on personal reasons. The paper differentiates between using different travel possibilities in the OSA problem, such as using company assigned or a company owned vehicles, private vehicles or using public transport, if needed. Also, a user-friendly web application was made and is available to the public for testing purposes.


Refereed Proceedings

  1. R. Čorić, M. Đumić, D. Jakobović, Complexity Comparison of Integer Programming and Genetic Algorithms for Resource Constrained Scheduling Problems , 40th International ICT Convention - MIPRO 2017, Opatija, 2017, 1394-1400
    Resource constrained project scheduling problem (RCPSP) is one of the most intractable combinatorial optimization problems. RCPSP belongs to the class of NP hard problems. Integer Programming (IP) is one of the exact solving methods that can be used for solving RCPSP. IP formulation uses binary decision variables for generating a feasible solution and with different boundaries eliminates some of solutions to reduce the solution space size. All exact methods, including IP, search through entire solution space so they are impractical for very large problem instances. Due to the fact that exact methods are not applicable to all problem instances, many heuristic approaches are developed, such as genetic algorithms. In this paper we compare the time complexity of IP formulations and genetic algorithms when solving the RCPSP. In this paper we use two different solution representations for genetic algorithms, permutation vector and vector of floating point numbers. Two formulations of IP and and their time and convergence results are compared for the aforementioned approaches.


Others

  1. M. Đumić, M. Jukić Bokun, Euklidov algoritam, Osječki matematički list 13 (2013), 121-137



Professional Activities

Conferences
  • 15th International Conference on Operational Research KOI 2014, Osijek, Croatia, September 24-26, 2014.
  • 40th International ICT Convention - MIPRO 2017, Opatija, Croatia, May 22-26, 2017.

 

Schools
  • 7th PhD Summer School in Discrete Mathematics, Rogla, Slovenia, July 23-29, 2017.
  • COST Action Training School: Improving Applicability of Nature-Inspired Optimisation Joining Theory and Practice, Paris, France, October 18-24, 2017.

 

Service Activities
  • Festival znanosti:

2011. radionica - Primjena Sunčeve svjetlosti pri određenim izračunavanjima

2012. radionica - 10 u svijetu matematike

2013. radionica - Zamisli jedan broj

2015. radionica - Kakve veze ima Sunce s matematikom?

  • Zimska škola matematike:

2011. predavanje - Euklidov algoritam

  • Zimska škola informatike:

2017. radionica - Multi-threading i multi-processing u Pythonu

 


Teaching

Nastavne aktivnosti u zimskom semestru akademske 2017./2018.

 

Nastavne aktivnosti u ljetnom semestru akademske 2017./2018.

 

Nastavne aktivnosti u prošlosti:

  • Analitička geometrija
  • Kombinatorna i diskretna matematika
  • Uvod u računarstvo

 

Konzultacije (Office Hours): Četvrtkom u 12:30 i po dogovoru.