A considerable part of educational systems tends to be online and computer oriented. However, online examination may create some difficulties during the evaluation of student performance. Process mining which arises as a new concept presents various powerful techniques for processing and analyzing different types of data by making use of some advanced information technologies. This paper proposes a novel approach based on process mining for evaluating the performance of students that should follow certain tasks on the computer. The proposed approach is composed of two main phases which are process mining and similarity analysis. Automatic assessment is performed totally in six steps in order to obtain students’ final grades. In addition, cheat control is possible in the last step thanks to the similarity analysis. A real‐life application in an Enterprise Resource Planning (ERP) course is performed in order to present usefulness, validity and practicality of the proposed approach. Furthermore, to evaluate the performance of the assessment system, we compared the assessment mechanism against instructor. A total of 15 students’ answers belonging to computer‐aided exam are assessed by instructor and the results showed a very good agreement between the automatic assessment system and instructor.

No abstract

No abstract

This paper considers the general lot sizing and scheduling problem (GLSP) in single level capacitated environments with sequence dependent item changeovers. The proposed model simultaneously determines the production sequence of multiple items with capacity-constrained dynamic demand and lot size to minimize overall costs. First, a mixed-integer programming (MIP) model for the GLSP is developed in order to solve smaller size problems. Afterwards, a matheuristic algorithm that integrates Simulated Annealing (SA) algorithm and the proposed MIP model is devised for solving larger size problems. The proposed matheuristic approach decomposes the GLSP into sub-problems. The proposed SA algorithm plays the controller role. It guides the search process by determining values for some of the decision variables and calls the MIP model to identify the optimal values for the remaining decision variables at each iteration. Extensive numerical experiments on randomly generated test instances are performed in order to evaluate the performance of the proposed matheuristic method. It is observed that the proposed matheuristic based solution method outperforms the MIP and SA, if they are used alone for solving the present GLSP.

Geleneksel kısıtlandırılmış parti büyüklüğü belirleme problemi işletmelerde sıklıkla karşılaşılan problemlerden biridir. Ancak, bu problemlerin modellenme aşamasında gerçek hayatta geçerli olabilen pek çok faktör dikkate alınmamaktadır. Bu çalışmada, sipariş üzerine kağıt/karton çanta üretimi yapan bir işletmedeki bütünleşik parti büyüklüğü belirleme ve çizelgeleme problemi modellenerek çözümlenmiştir. Problem için karışık tam sayılı programlama modeli önerilmiştir. Önerilen modelde, ürünler arası geçişlerde ve üretim periyotlarındaki hazırlık süreleri ve maliyetleri göz önünde bulundurulmuştur. Geliştirilen model, üretim maliyeti, elde tutma maliyeti, karşılanamayan talep maliyeti, dışardan satın alma maliyeti ve sıra bağımlı ürün geçişlerinin hazırlık maliyeti toplamını en küçüklemeyi hedeflemektedir. Geliştirilen modelin uygulamasıyla, üretim kaynaklarının daha verimli kullanılıp daha efektif üretim planlarının ortaya konulabileceği görülmüştür.