Özsakalli, Gökberk

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Profile URL
https://gcris.yasar.edu.tr/handle/123456789/12271
Name Variants
Job Title
Araş.Gör.
Email Address
Main Affiliation
01.01.06.03. Lojistik Yönetimi Bölümü
Status
Former Staff
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ORCID ID
Scopus Author ID
56460368100
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Google Scholar ID
WoS Researcher ID
MBR-6229-2025

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1

Scopus Citation Count

4

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0.50

Scopus Citations per Publication

2.00

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1

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24th International Symposium for Production Research ISPR 20241
Journal of Applied Research and Technology1
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    Article
    Citation - WoS: 1
    Citation - Scopus: 4
    Daily logistics planning with multiple 3PLs: A case study in a chemical company
    (Universidad Nacional Autonoma de Mexico Centro de Ciencias Aplicadas y Desarrollo Tecnologico, 2014) Gökberk Ozsakalli; Deniz Özdemir; Sel Ozcan; B. Sarioglu; A. Dincer; Ozsakalli, G.; Dincer, A.; Ozcan, S.; Ozdemir, D.; Sarioglu, B.
    The importance of efficient logistics management for chemical industry considered to be one of the important issues in process industries. Motivated from a chemical factory operating in Turkey cost efficient daily logistics planning using multiple third party logistics providers (3PL) with different contracting schemes are analyzed. In order to reduce planning time and maximize the physical vehicle capacity utilization problem of the company is formulated as a mixed integer mathematical model and a two-phase solution approach is proposed. Using the real life daily shipment requirement data the proposed model and the solution methodology is tested. Furthermore impact of various company practices and types of different transportation pricing schemes are analyzed to better design 3PL contracts. The initial results are very promising where optimum solution for large scaled problem can be obtained in seconds and the daily shipment planning can be updated dynamically whenever it is necessary. The analysis indicates that cost savings through holistic planning is robust to contracting schemes and specific clauses are not always needed to guarantee certain service quality. We believe that the efficiency achieved through the integration of such techniques can become highly attractive for further applications in the industry. © 2021 Elsevier B.V. All rights reserved.
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    Conference Object
    Mixed-Integer and Constraint Programming Approaches for Determination of Locations of Long-Term Care Facilities
    (Springer Science and Business Media Deutschland GmbH, 2025) Mert Paldrak; Gamze Erdem; Gökberk Ozsakalli; Armağan Yağız Terim; Özsakallı, Gökberk; Paldrak, Mert; Terim, Armaǧan Yaǧız; Erdem, Gamze; N.M. Durakbasa , K.G. Gülen
    This study addresses the Long-Term Care Facility Location Problem (LTCFLP) focusing on the optimal location of long-term care facilities in İzmir Turkiye. Long-term care facilities often referred to as nursing homes provide medical services and daily assistance to individuals primarily the elderly over extended periods. As the aging population increasing globally the demand for such facilities has grown prompting governments to invest in their development. This research aims to determine the best locations for these facilities balance the load across facilities and o minimize both the establishment and patient assignment costs. The problem is formulated as a multi-objective optimization model considering facility capacity overcapacity allowance and facility utilization. A mixed-integer programming model is developed to achieve these objectives. Additionally a novel contribution is made by applying a constraint programming (CP) approach which has not been used for LTCFLP before. The study compares the results from both mixed-integer programming (MIP) and constraint programming models to evaluate their efficiency and effectiveness in solving this complex real-world problem. The results highlight the trade-offs between different models and propose future research directions for enhancing facility location planning. © 2025 Elsevier B.V. All rights reserved.