Erdem, Mehmet

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Erdem, M.
Erdem,M.
Erdem, Mehmet
M., Erdem
E.,Mehmet
Mehmet, Erdem
E., Mehmet
M.,Erdem
Job Title
Doktor Öğretim Üyesi
Email Address
mehmet.erdem@atilim.edu.tr
Main Affiliation
Industrial Engineering
Status
Former Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

2

ZERO HUNGER
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0

Research Products

14

LIFE BELOW WATER
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0

Research Products

17

PARTNERSHIPS FOR THE GOALS
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0

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5

GENDER EQUALITY
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0

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16

PEACE, JUSTICE AND STRONG INSTITUTIONS
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0

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8

DECENT WORK AND ECONOMIC GROWTH
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0

Research Products

4

QUALITY EDUCATION
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0

Research Products

6

CLEAN WATER AND SANITATION
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0

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7

AFFORDABLE AND CLEAN ENERGY
AFFORDABLE AND CLEAN ENERGY Logo

2

Research Products

10

REDUCED INEQUALITIES
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0

Research Products

11

SUSTAINABLE CITIES AND COMMUNITIES
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2

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9

INDUSTRY, INNOVATION AND INFRASTRUCTURE
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0

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1

NO POVERTY
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0

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3

GOOD HEALTH AND WELL-BEING
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0

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12

RESPONSIBLE CONSUMPTION AND PRODUCTION
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1

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13

CLIMATE ACTION
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2

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15

LIFE ON LAND
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0

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This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

4

Articles

4

Views / Downloads

0/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

170

Scopus Citation Count

193

WoS h-index

3

Scopus h-index

3

Patents

0

Projects

0

WoS Citations per Publication

42.50

Scopus Citations per Publication

48.25

Open Access Source

2

Supervised Theses

0

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JournalCount
Journal of Cleaner Production1
Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi1
South African Journal of Industrial Engineering1
Sustainable Cities and Society1
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  • Article
    Citation - WoS: 61
    Citation - Scopus: 68
    Analysis of Electric Vehicles in Home Health Care Routing Problem
    (Elsevier Sci Ltd, 2019) Erdem, Mehmet; Koc, Cagri
    The road transportation is one of the largest contributors to greenhouse gas emissions globally, and rapid urbanisation increases the environmental and economic challenges. Electric vehicles support green supply chain and clean routing operations when compared with the traditional fossil fuel-powered vehicles. This paper analyses a variant of the home health care routing problem in which a group of health care workers performs a requested number of jobs by using electric vehicles. The problem considers multi-depot, heterogeneous fleet, time windows, preferences, competencies, connected activities, the range of electric vehicles, charging status, and charge strategies. We develop a hybrid metaheuristic which successfully combines genetic algorithm and a variable neighbourhood descent, and offer several algorithmic procedures tailored to handle the rich constraints of the problem. Extensive computational experiments on small, medium and large-scale instances have shown that the hybrid metaheuristic is effective on the problem. (C) 2019 Elsevier Ltd. All rights reserved.