Toktaş Palut, Peral

Profile URL:
Email Address:palutp@mef.edu.tr
Main Affiliation:02.01. Department of Industrial Engineering
Status: Current Staff
ORCID:ORCID Profile0000-0002-8864-0904
Scopus ID:Scopus Profile48361959000
Web of Science ID:Web of Science ProfileKIW-9302-2024
Name Variants:
Toktaş Palut, Peral Toktas Palut, P.
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2025 - 20262

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Author of Publication: search.filters.isAuthorOfPublication.21a1f5b0-bc64-44cf-aafe-59ec8d8b76fa

Scholarly Output Search Results

Now showing 1 - 2 of 2
  • Article
    Empowering Electric Vehicle Adoption: Innovative Strategies for Optimizing Charging Station Placement Based on Projected Demand
    (Wiley, 2025) Cekyay, Bora; Kabak, Ozgur; Ozaydin, Ozay; Isik, Mine; Toktas-Palut, Peral; Topcu, Y. Ilker; Ulengin, Fusun
    Electric vehicles (EVs) are pivotal for reducing transportation-related emissions; however, the lack of adequate charging infrastructure remains a significant barrier to their widespread adoption. This study presents a comprehensive methodology for optimizing EV charging station placement. It combines a gravity model, scenario analysis, and mixed-integer linear programming (MILP) to ensure a thorough and robust approach. The model aims to maximize accessibility by ensuring both path-level and overall system demand coverage across diverse scenarios, providing reassurance about the validity of the findings. The methodology is tested on the Bursa-& Idot;zmir motorway in Turkey, a strategic intercity route with rapidly growing EV penetration. Results reveal that the optimal configuration involves locating charging stations in seven of the nine service areas. This allocation secures a minimum path coverage ratio of 0.903, meaning 90.3% of the route is covered by charging stations, and an overall demand coverage ratio of 0.935, indicating that 93.5% of total demand is covered across all scenarios. A sensitivity analysis further shows that increasing the network to 45 chargers elevates reachability levels to above 97%, indicating the infrastructure scale required for reliable service quality. The findings underscore the practical applicability of the proposed framework, providing policymakers and infrastructure planners with robust, data-driven guidance for charging network expansion. By integrating demand forecasting with resilient optimization, this study advances both methodological and empirical insights, empowering the audience to make informed decisions for sustainable EV adoption.
  • Book Part
    Citation - Scopus: 1
    Critical Social Perspectives on Automation and Job Impacts
    (Elsevier, 2026) Toktaş-Palut, Peral

Research Topics

Domains
Social Sciences
Fields
Business, Management and AccountingEconomics, Econometrics and FinanceDecision Sciences
Subfields
Strategy and ManagementGeneral Economics, Econometrics and FinanceManagement Information SystemsInformation Systems and Management
Specific Research Areas
Sustainable Supply Chain Management
Global trade and economics
Supply Chain and Inventory Management
Global Trade and Competitiveness
Technology Adoption and User Behaviour

Sustainable Development Goals

PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
1
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
1
Research Products
Documents

14

Citations

339

h-index

7

Go to Scopus profile
Documents

11

Citations

249

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Publication Collaboration

Affiliation Name Count
Doğuş University 13
Sabancı Üniversitesi 4
Istanbul Technical University 4
Maltepe University 2
Yeditepe University 1
1 / 2
Data obtained from OpenAlex
JournalCount
Industry 4.0 and Sustainability: Integrating Digital Technologies and Circular Models for a Sustainable Future1
Journal of Advanced Transportation1
Current Page: 1 / 1
Scholarly Output

2

Articles

1

Views / Downloads

6/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

0

Scopus Citation Count

1

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.50

Open Access Source

1

Supervised Theses

0

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud