Browsing by Author "Tacoglu, Melis Tan"

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Citation - WoS: 2
Citation - Scopus: 5
A Literature Review on Supplier Selection Problem and Fuzzy Logic
(SPRINGER INTERNATIONAL PUBLISHING AG, 2022) Mert Paldrak; Gamze Erdem; Melis Tan Tacoglu; Simge Guclukol; Efthimia Staiou; Tan Tacoğlu, Melis; Paldrak, Mert; Guclukol, Simge; Staiou, Efthimia; Tacoglu, Melis Tan; Erdem, Gamze; C Kahraman; AC Tolga; SC Onar; S Cebi; B Oztaysi; IU Sari
Given the recent increasing competition in global market supplier selection and evaluation has attracted a great deal of attention especially at academic levels. Supplier selection problem is a complex problem since there exist a great number of unpredictable and uncontrollable factors which have a huge impact on decision-making process. Due to this complexity there are several criteria that must be taken into consideration such as cost quality on-time delivery proximity of suppliers long-term relationship etc. Although some of these criteria (quantitative) can be expressed using pure numeric scales some (qualitative) are linguistic due to the human assessments which contain some degree of subjectivity. Since involvement of human assessment causes vagueness for deterministic models the authors apply fuzzy logic which enables the decision makers to be able to convert their linguistic expressions into fuzzy numbers with the help of fuzzy membership functions. Considering that fuzzy logic plays a vital role in solving multi-criteria supplier selection problem this paper aims to present a review of supplier selection problem and its relation with fuzzy logic. In this paper several studies that highlight supplier selection problem and the importance of fuzzy logic involvement in the problem have been reviewed. An analysis of multi-criteria decision-making methods for supplier selection problem is conducted.
A Multi-objective Approach to Flight Scheduling and Fleet Assignment in Hub Network
(Springer, 2025) Melis Tan Tacoglu; Mustafa Arslan Ornek; Cemalettin Öztürk; Ornek, Mustafa Arslan; Ozturk, Cemalettin; Tacoglu, Melis Tan
The hub-and-spoke (HS) network is a widely used business strategy by airlines to optimize their operations and increase their reach by connecting multiple destinations through a central hub and the majority of the passengers are transit passengers. The airline schedule planning process starts with the flight scheduling problem (FSP) to generate a timetable in advance of six months. Then the fleet assignment problem (FAP) is examined to determine aircraft types. This sequential solution approach causes suboptimal solutions and the schedule must be adjusted to increased demand. Due to the complexity of this problem this study focuses specifically on incremental schedule design with one hub two-flight leg network. This study presents a Multi-Objective Mixed Integer Programming Model for integrated FSP and FAP to adjust the generated timetable with launching new flights. Two solution approaches are proposed to decide the new proposed flight’s time aircraft type and passenger assignment: the Weighted Goal Programming Model (WGPM) and the Lexicographic Goal Programming Model (LGPM). This study shows that there is a conflicting relationship between cost and C02 emissions in the flight scheduling process. If carbon dioxide emissions are prioritized airlines need to schedule more flights with small-capacity aircraft. © 2025 Elsevier B.V. All rights reserved.
A Survey on Optimization Problems in the Airline Industry and Airports
(SPRINGER INTERNATIONAL PUBLISHING AG, 2024) Mert Paldrak; Melis Tan Tacoglu; Mustafa Arslan Ornek; Paldrak, Mert; Ornek, Mustafa Arslan; Tacoglu, Melis Tan; C Kahraman; SC Onar; S Cebi; B Oztaysi; AC Tolga; IU Sari
In response to the rapid growth in air transportation demand the methods to manage allocate and efficiently use scarce resources in the airport play a vital role in improving the efficiency of the air transportation system. Due to the limited infrastructure of hub-and-spoke airports which is influenced by many factors the chief goal of the airline industry and airport management is to utilize such resources as check-in desks departure lounges bridge-equipped gates aircraft stands baggage carousels staff and equipment. Based on the mobility of the resources in the airports there are two types of problems in the airline industry and airports namely mobile and immobile resource optimization problems. The crew optimization problems are mobile resource optimization problems whereas airport gate assignment counter assignment problems and carousel optimization problems are immobile resource optimization problems in airports. Considering the problems classified based on the mobility of the resources this paper aims to present a survey of optimization problems in the aviation industry explaining the interplay and relationship between these problems along with modeling techniques and proposed solutions to this individual problem.
Fuzzy Model for Multi-objective Airport Gate Assignment Problem
(Springer Science and Business Media Deutschland GmbH, 2023) Mert Paldrak; Melis Tan Tacoglu; Mustafa Arslan Ornek; Paldrak, Mert; Örnek, Mustafa Arslan; Tacoglu, Melis Tan; C. Kahraman , I.U. Sari , B. Oztaysi , S. Cevik Onar , S. Cebi , A.C. Tolga
To address the increasing demand for air transportation the management allocation and efficient utilization of limited airport resources such as bridge-equipped gates are of paramount importance to improve the efficiency of the air transportation system. Bridge-equipped gates are scarce and immobile resources have a significant impact on airport management airlines and passenger convenience when utilized properly. Hence the gate assignment problem is an important problem involving multiple stakeholders with conflicting objectives. This study proposes a fuzzy model to tackle two objectives: maximization of overall utility of flight-gate assignments and maximization of the robustness of the assignment schedule simultaneously. Fuzzy variables are employed in order to represent the uncertainty of idle times between two consecutive flights served by the same bridge-equipped gate and their membership degrees express their effect on assignment robustness. An adjustment function is applied to combine these two objective functions into one. To handle this NP-hard problem in a reasonable amount of computational time a constructive heuristic algorithm is employed. The performance of the proposed fuzzy model is evaluated with the help of various test in instances of different sizes Two fuzzy distribution functions are tested and their comparison is provided. The simulation results demonstrate the applicability and effectiveness of the fuzzy model in addressing multi-objective airport gate assignment problem. © 2023 Elsevier B.V. All rights reserved.
Fuzzy TOPSIS and Goal Programming Approaches to Multi Objective Facility Location Problem for Emergency Goods and Services Distribution and Bornova/Izmir Case Study
(Springer Science and Business Media Deutschland GmbH, 2022) Mert Paldrak; Simge Güçlükol Ergin; Mahmut Ali Gökçe; Melis Tan Tacoglu; Gökçe, Mahmut Ali; Tan Tacoğlu, Melis; Paldrak, Mert; Güçlükol, Simge; Tacoglu, Melis Tan; C. Kahraman , S. Cevik Onar , B. Oztaysi , I.U. Sari , A.C. Tolga , S. Cebi
Distributions of vital goods and services in emergency or post disaster situations are of paramount importance to be able to meet the requirements of those in need on time. Finding an appropriate location for facilities to distribute such goods and services efficiently and quickly is an important challenge. In such a situation location decisions for these facilities must be made quickly considering multiple objectives. This problem is a multi-objective facility location problem (MOFLP). The main focus of this study is to present two solution methodologies for a MOFLP in a post disaster situation. We specifically consider objective of minimizing maximum weighted distance traveled and minimizing total cost of facilities to be opened in order to satisfy all demand. We also provide a version of the problem when the number of facilities to be opened is limited and second objective becomes maximizing demand covered. Due to the conflicting nature of the objective functions we propose to apply Fuzzy TOPSIS and Goal Programming and compare the solutions obtained using these two techniques with respect to solution quality and computational time. We present the developed models and provide results from a real-life application using existing emergency assembly areas and current census data for Bornova/İzmir. This paper contributes in two ways to existing literature. First is the comparison between multiple (two) solution methodologies for MOPLP. Studies in the literature provide only one solution technique such as Fuzzy TOPSIS Goal Programming etc. Secondly we implement these methodologies by using real life data for emergency situations. © 2022 Elsevier B.V. All rights reserved.
Genetic Algorithm and Mathematical Modelling for Integrated Schedule Design and Fleet Assignment at a Mega-Hub
(Multidisciplinary Digital Publishing Institute (MDPI), 2025) Melis Tan Tacoglu; Mustafa Arslan Ornek; Yigit Kazancoglu; Tan Tacoglu, Melis; Ornek, Mustafa Arslan; Tacoglu, Melis Tan; Kazancoglu, Yigit
Airline networks are becoming increasingly complex particularly at mega-hub airports characterized by high transit volumes. Effective schedule design and fleet assignment are critical for an airline as they directly influence passenger connectivity and profitability. This study addresses the challenge of introducing a new route from a mega-hub to a new destination while maintaining the existing flight network and leveraging arrivals from spoke airports to ensure connectivity. First a mixed-integer nonlinear mathematical model was formulated to produce a global optimal solution at a lower time granularity but it became computationally intractable at higher granularities due to the exponential growth in constraints and variables. Second a genetic algorithm (GA) was employed to demonstrate scalability and flexibility delivering near-optimal high-granularity schedules with significantly reduced computational time. Empirical validation using real-world data from 37 spoke airports revealed that while the exact model minimized waiting times and maximized profit at lower granularity the GA provided nearly comparable profit at higher granularity. These findings guide airline managers seeking to optimize passenger connectivity and cost efficiency in competitive global markets. © 2025 Elsevier B.V. All rights reserved.
Citation - WoS: 2
Citation - Scopus: 2
Heuristic methods for integrated incremental schedule design and fleet assignment problem for hub and spoke network
(Inderscience Publishers, 2024) Melis Tan Tacoglu; Mustafa Arslan Ornek; Yigit Kazancoglu; Ornek, M. Arslan; Tacoglu, Melis Tan; Kazancoglu, Yigit
Managing airline inbound and outbound schedules among passenger demand and aircraft utility complexity are addressed through three proposed heuristic methods for integrated schedule design and fleet assignment problem (ISDFAP) in single-hub two-flight leg hub-and-spoke networks. The second heuristic considering waiting time and available seat capacity contrasts with the first focusing only on waiting time for passenger-flight assignments. Meanwhile the third heuristic considers aircraft buffer time and stay time restrictions at the destination. Comparing the first two heuristics reveals that considering seat availability does not reduce waiting time. Flight departure time adjustments and overall timetable changes depend significantly on buffer time and wait time criteria. © 2024 Elsevier B.V. All rights reserved.