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YAĞMAHAN, BETÜL

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YAĞMAHAN

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BETÜL

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2015 - 201912020 - 20222
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    Range coverage location model: An optimization model for the charging station location problem in a transportation network to cover intercity travels
    (Wiley, 2021-09-14) Yılmaz Hilal; Yağmahan, Betül; Yılmaz Hilal; YAĞMAHAN, BETÜL; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü; 0000-0003-1744-3062; 0000-0001-8125-6814; GZG-5051-2022; B-5557-2017
    Equipping highways with charging stations (CSs) is a fundamental step for travelling with electric vehicles (EVs) between cities and countries conveniently. This article focuses on locating CSs to fully connect roads that may require multiple charging events by considering the minimum driving range for all possible paths in a transportation network. For this purpose, we present a new binary integer linear programming model named the Range Coverage Location Model (RCLM) to find the minimum required CSs and their locations that the driving range can cover without defining the paths in the network. By adding the result of RCLM as a constraint to the model, the optimum locations that maximize the EV flows are determined with the RCLM-Max model. Two versions of the RCLM are introduced. The link-based RCLM is designed for problems in which there are CSs in each of the origin/destination (OD) nodes (intersections), while the network-based RCLM aims to connect links without stopping by the OD nodes, making the model stricter but convenient for EV travels. The proposed models are validated through extensive computational experiments with real data from a highway network in Turkey. The experiments show that RCLM and RCLM-Max can solve very large-scale problems in a very short CPU time. The findings suggest that the link-based RCLM can be applied when the budget is at the forefront, and the network-based model is preferred if the aim is to connect the main roads without stopping by the OD nodes.
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    Publication
    Mixed-model assembly line balancing with smoothing approach based on tabu search algorithm
    (Gazi Üniversitesi, 2015-01-01) Yağmahan, Betül; Emel, Erdal; YAĞMAHAN, BETÜL; EMEL, ERDAL; Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü; 0000-0003-1744-3062; 0000-0002-9220-7353; N-8691-2014; B-5557-2017
    Mixed-model assembly lines are needed for the assembly of products with a variety of models at comparatively lower costs. The design of such lines requires the work to be done at stations well balanced, satisfying the constraints such as time, space and location for optimal productivity and efficiency. This paper presents a heuristic algorithm for the mixed-model assembly line balancing problem to minimize the number of stations for a given cycle time. The proposed algorithm further reduces time discrepancies among stations due to differences in times for common operations of different models by using a smoothing approach which is based on the tabu search algorithm.
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    Publication
    An integrated ranking approach based on group multi-criteria decision making and sensitivity analysis to evaluate charging stations under sustainability
    (Springer, 2022-01-20) Yağmahan, Betül; YAĞMAHAN, BETÜL; Yılmaz, Hilal; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi; 0000-0003-1744-3062; GZG-5051-2022; B-5557-2017
    The increasing environmental pollution has led to the need to accelerate interest in electric vehicles. It is crucial to specify locations for electric vehicle charging stations (EVCSs) to meet the charge demand. The question that arises here is how to make a comprehensive evaluation of the alternative EVCS locations regarding sustainability. This study presents a new integrated group multi-criteria decision making (MCDM) approach for a robust evaluation of alternative EVCS locations. Two different group aggregation techniques (GATs) are applied to obtain the aggregated weights with AHP (analytical hierarchy process): aggregating individual judgments and aggregating individual priorities. For ranking alternative locations, two MCDM methods, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and MOORA (Multi-Objective Optimization on the Basis of Ratio Analysis) were applied for both aggregated weights. Furthermore, we introduce two types of rankings from the sensitivity analysis based on the most selected alternatives for each rank position and the most selected rank position for each alternative. Finally, an integrated ranking is obtained by combining the results of group MCDM methods and sensitivity analysis to investigate the impact of GATs and MCDM methods. The proposed methodology is applied to rank the EVCS locations in Bursa, Turkey, with four main criteria and eight sub-criteria. The similarity measure results indicate that the GAT and the MCDM method have an impact on the evaluation scores and the rankings. The integrated group MCDM approach provides a comprehensive evaluation of the alternatives.