Misiç, Arya

Profile Picture
Profile URL
https://hdl.handle.net/20.500.14365/6766
Name Variants
Misic, Arya
Misic, Sevgen Arya
Misiç, Arya
Sevgen, Arya
Misiç, Sevgen Arya
Misiç Sevgen, Arya
Job Title
Email Address
aryasevgen@gmail.com
arya.sevgen@ieu.edu.tr
Main Affiliation
05.09. Industrial Engineering
Status
Current Staff
Website
ORCID ID
0000-0002-8543-9025
Scopus Author ID
57201060461
Turkish CoHE Profile ID
24A0B2DCA4B5DC61
Google Scholar ID
eLMs-I0AAAAJ
WoS Researcher ID
AGU-7294-2022
Files
IMG_0803.jpeg (1.27 MB)

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
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GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
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QUALITY EDUCATION4
QUALITY EDUCATION
0
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GENDER EQUALITY5
GENDER EQUALITY
0
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CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
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AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
2
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DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
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INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
0
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REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
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SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
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RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
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CLIMATE ACTION13
CLIMATE ACTION
1
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LIFE BELOW WATER14
LIFE BELOW WATER
0
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LIFE ON LAND15
LIFE ON LAND
0
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PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
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PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents

5

Citations

18

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2

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Documents

3

Citations

13

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Scholarly Output

4

Articles

2

Views / Downloads

6/16

Supervised MSc Theses

1

Supervised PhD Theses

0

WoS Citation Count

3

Scopus Citation Count

5

Patents

0

Projects

0

WoS Citations per Publication

0.75

Scopus Citations per Publication

1.25

Open Access Source

3

Supervised Theses

1

JournalCount
2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 2024 Innovations in Intelligent Systems and Applications Conference, ASYU 2024 -- 16 October 2024 through 18 October 2024 -- Ankara -- 2045621
Computers and Industrial Engineering1
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  • Thumbnail Image
    Conference Object
    Applying Genetic Algorithms To the Identical Parallel Machine Scheduling Problem
    (Institute of Electrical and Electronics Engineers Inc., 2024) Oğuz, K.; Altuner, B.; Anar, C.; Reisoğlu, E.; Karaca, M.N.; Sevgen, Arya; Misiç, Arya Sevgen
    We are proposing an evolutionary approach to the identical parallel machine scheduling problem using a novel representation for genetic algorithms. The genetic algorithm is compared to the mathematical model of the problem. Both of the approaches are implemented in Python using related libraries. The results show that, specially for the larger instances of the problem, the genetic algorithm performs better; it finds an appropriate solution with low tardiness values in minutes, rather than hours when the mathematical model is used. Our study shows that genetic algorithms a valid approach for finding solutions to the identical parallel machine scheduling problem. © 2024 IEEE.
  • Thumbnail Image
    Article
    Citation - WoS: 1
    Citation - Scopus: 3
    Energy Storage and Transmission Line Design for an Island System With Renewable Power
    (Pergamon-elsevier Science Ltd, 2025) Sevgen, Arya; Karatas, Mumtaz; Dasci, Abdullah; Misic, Arya Sevgen
    This paper addresses an energy system design problem for an island system that relies on renewable sources such as wind or solar PV. Typically disconnected from main grids, island systems, i.e., small islands or remote areas, often resort to costly power generation sources such as diesel. The design problem considered here includes the capacity decisions of energy storage systems (ESSs) and transmission lines that minimize total annual operation and investment costs. To address this challenge, we first introduce a deterministic mixed-integer linear program that is immediately extended to consider the stochastic demand and renewable generation via sample average approximation method. We implement our model on a case partly based on El Hierro, a small island in the Canary Islands of Spain. Through our experimental analysis, we generate a number of managerial insights into system design decisions and operational outcomes under a variety of storage characteristics, renewable sources, and spatial considerations.