Tedarikçi ilişkilerinde tedarikçi seçim kararı bir işletmenin en önemli başarı faktörlerinden biridir. Bu çalışmanın amacı yeşil tedarikçi seçiminin klasik tedarikçi seçimi ile olan farklılığını ve önemini ortaya koymaktır. Doğu Marmara bölgesinde makina imalatı sektöründe yer alan firmaların tedarikçi seçimi incelenmiştir. Anket yöntemi ile yeşil tedarikçi seçim kriterleri belirlenmiş ve önerilen kriterlerle yeşil tedarikçi seçimi AHP ve Bulanık AHP yöntemleri kullanılarak belirlenmiştir. Klasik tedarikçi seçim kriterleri ile de tedarikçi seçimi yapılmıştır. Yeşil kriterle elde edilen sonuç klasik kriterler ile yapılan tedarikçi seçiminden farklı olmuştur. Bu çalışma firmalar tarafından seçim yöntemlerinin kullanılabilirliğini ve sektör için yeşil kriterlerin belirlenmesine katkıda bulunmaktadır.

A two-stage cold supply chain manages the transportation, storage, and distribution of temperature-sensitive products like frozen food, fresh/green products, and pharmaceuticals, which makes it costly. It consists of three key elements: a supplier, a warehouse, and multiple customers. Procurement planning can be conducted for various products, and this study assumes the transport of a fresh/green product with gradually decreasing quality due to its perishable nature. In a two-stage cold supply chain, multiple objective functions can be defined, including cost minimization, product quality optimization, and transportation/storage condition optimization. We developed a mathematical model to optimize these objectives, incorporating two specific functions, cost minimization and product age reduction, to ensure efficient supply chain performance. Traditional solution methods often struggle with multi-objective mathematical models due to their complexity. Therefore, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a Genetic Algorithm-based approach, was applied to solve the model efficiently. NSGA-II optimized planning for a 7-day period under specific demand conditions, ensuring better resource allocation. The results showed that NSGA-II was better than traditional methods at making decisions and routing efficiently in the two-stage cold supply chain. This led to much better outcomes, with lower costs, less waste, and better product quality throughout the process.

Storage operations, order-picking, and product-handling processes have become increasingly important in today’s industrial environment. These operations are a huge burden for businesses in terms of time and cost, but they often do not add direct value to products or services. Therefore, it has become essential to improve the storage operations to the highest quality, reduce the costs arising from storage, and increase customer satisfaction. This study compared genetic algorithm (GA) and simulated annealing (SA) methods with existing real results and operations in order to minimize the distance traveled by the picker in order-picking systems, optimize routes, and increase operational efficiency in the medical textile industry. In the analyses conducted on product-based, list-based, and order-based strategies, real data sets were used to examine the performance of both methods in detail. The study results revealed that GA reduced the total travel distance by 50% and reduced the total number of tours from 51 to 32. In addition, the SA method provided efficient results in certain scenarios, but GA showed superior performance in terms of minimizing the distance and number of tours. While the product-based strategy provided the best results regarding travel distance and number of tours, the list-based approach showed a balanced performance. The study offers significant improvement potential in logistics operations by reducing distances by up to 37% and increasing operational efficiency by up to 50% in order-picking processes.

Learning objectives: The most important problem of dynamic societies is waste management (WM). For a healthy, happy and sustainable life, WM in cities should be carried out accurately, quickly and effectively with artificial intelligence-based systems. The most important negative output of developed societies is waste, the more production and consumption is made, the more waste will be generated. Based on the principle of Green energy, where and what kind of work should be done in WM will be put forward by practices.

Vocational education can create a reliable environment for both employees and employers. It allows companies to target niche markets, provide valuable content and networking opportunities. However, there is still a need to increase awareness and popularization of vocational education in industries. Vocational education is carried out by authorized institutions and is an activity that requires considerable cost and time. In this study, the factors affecting the exam performance of the candidates participating in the Vocational Qualification Certificate exams are examined. The research population consists of candidates who participated in the examination of the Bridge Crane Operator profession. Random sampling method was preferred in the selection of exams. 38-question survey was administered to 84 participants who took the exams. This analysis aims to increase awareness of the Professional Competence Certificate and to determine the factors affecting the exam performance of the candidates participating in the exam. By determining the factors, it is aimed to reduce the costs of repeating the exam after the failed exam and to prevent loss of time for both the institution conducting the exam and the candidate taking the exam. ANOVA analysis was used to measure the level of significance between demographic data and factors affecting exam performance.