Wos Açık Erişimli Yayınlar

Permanent URI for this collectionhttps://hdl.handle.net/11727/10754

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Author: search.filters.author.Dengiz, Bernasearch.filters.applied.f.publicationcategory: search.filters.publicationcategory.Makale - Uluslararası Hakemli Dergi

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    A New Multi-Echelon Repair Network Model with Multiple Upstream Locations for Level of Repair Analysis Problem
    (2021) Bicakci, Ismail; Ic, Yusuf Tansel; Karasakal, Esra; Dengiz, Berna; 0000-0001-9274-7467; AGE-3003-2022
    Level of repair analysis (LORA) determines (1) the best decision during a malfunction of each product component; (2) the location in the repair network to perform the decision and (3) the quantity of required resources in each facility. Capital goods have long life cycles and their total life cycle costs are extremely high. LORA, which can be done repeatedly during the life cycle of the product, both at design and product support phase, plays an important role in minimising the total life cycle costs of capital goods. It is mostly applied to systems that operate in different geographical areas and deployed in different regions, which include different subsystems with special technology and expertise, and have a complex product structure. In this study, we propose a new mathematical model to the LORA problem, which is more comprehensive and flexible than the other pure LORA models in the literature. The proposed model uses the multiple upstream approach that allows the transfer of the components from a location in the lower echelon to the predefined locations in the upper echelon and determines the material movement paths between each facility, defining the facilities' locations in the repair network. The performance of the proposed model is tested on benchmark instances and the results are compared with the single upstream model. Computational experiments show that the proposed model is more effective than the single upstream model and reduces the total life cycle costs by 4.85% on average, which is an enormous cost saving when total life cycle costs of capital goods are considered.
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    Modified self-adaptive local search algorithm for a biobjective permutation flow shop scheduling problem
    (2019) Alabas Uslu, Cigdem; Dengiz, Berna; Aglan, Canan; Sabuncuoglu, Ihsan
    Interest in multiobjective permutation flow shop scheduling (PFSS) has increased in the last decade to ensure effective resource utilization. This study presents a modified self-adaptive local search (MSALS) algorithm for the biobjective permutation flow shop scheduling problem where both makespan and total flow time objectives are minimized. Compared to existing sophisticated heuristic algorithms, MSALS is quite simple to apply to different biobjective PFSS instances without requiring effort or time for parameter tuning. Computational experiments showed that MSALS is either superior to current heuristics for Pareto sets or is incomparable due to other performance indicators of multiobjective problems.