11 hasil untuk "Burak ERKAYMAN"
Menampilkan 1–11 · 0,18 detik · RSS
-
Artikel Jurnal Teks lengkap
Markov approach for inventory control with meta-heuristics in intermittent demand environment
Demand variability directly affects inventory management. The variability of intermittent demand causes high lost sales or holding costs. While lost sales reduce customer satisfaction, keeping excessive stock also creates high costs for companies. This situation can be prevented with an appropriate…
-
Artikel Jurnal
Hybrid AI models for multi-depot vehicle routing with split deliveries and multiple trips
Last-mile logistics operations in urban environments are becoming increasingly complex due to fragmented customer demands, multiple depots, vehicle capacity constraints, and the need for split deliveries across multiple trips. Classical optimization approaches often fail to address these…
-
Artikel Jurnal
Enhancing location accuracy in urban logistics using hybrid machine learning and deep learning models on large-scale global positioning system data
As technology advances, analyzing Global Positioning System (GPS) data is critical to improving location accuracy in product distribution. In this study, the geolocation accuracy of a distribution company in Istanbul was evaluated using 4,784,003 GPS records and prediction models, including machine…
-
Artikel Jurnal
An Integrated Fuzzy Approach for Strategic Alliance Partner Selection in Third-Party Logistics
Outsourcing some of the logistic activities is a useful strategy for companies in recent years. This makes it possible for firms to concentrate on their main issues and processes and presents facility to improve logistics performance, to reduce costs, and to improve quality. Therefore provider…
-
Artikel Jurnal
An effective AI infused demand forecasting application for automotive spare parts industry: a real case from Turkey
Abstract The accuracy of demand forecasting in the automotive spare parts industry is critical to operational efficiency and financial performance. However, the irregular nature of spare parts demand makes forecasting processes quite complex. As traditional forecasting methods are unable to model…
-
Artikel Jurnal
Increasing load factor in logistics and evaluating shipment performance with machine learning methods: A case from the automotive industry
Abstract The insufficient loading of vehicles, which leads to a low logistics load factor is a common problem in the logistics industry. This study addresses this issue by utilizing actual shipment data from an automotive company. An effective method has been proposed to improve the company’s…
-
Artikel Jurnal
Fleet Type Planning for Private Air Transport After Covid-19
The global impact of the epidemic COVID-19 has done great damage to air transport. Demand for airline transportation has declined for reasons such as quarantine practices by countries, curfews, the economic recession, and the transfer of meetings to digital platforms. This situation has also led to…
-
Artikel Jurnal
New Artificial intelligence approaches for brand switching decisions
The problem of customer complaints occurs in almost every business and solutions are offered to reduce these complaints. When companies do not pay necessary attention to the complaints, they suffer revenue losses due to the loss of customers, the brand and the company's image. In this study, based…
-
Artikel Jurnal
Application of the full consistency method (FUCOM) - Cosine similarity framework in 5G infrastructure investment planning: An approach for telecommunication quality improvements
In the rapidly evolving telecommunications landscape, the shift towards advanced communication technologies marks a critical milestone. This transition promises to revolutionize connectivity by enabling seamless data downloads, high-quality video streaming, and instant access to applications…