خلاصه‌سازی تک سندی متون فارسی به کمک یادگیری عمیق ماشینی
  •   آرشیو : نسخه زمستان 1397
  •   موضوع : هوش مصنوعی
  • نویسنده/گان : علیرضا محسنی ، ونوس مرضی، امیرحسین جدیدی نژاد
  •   کلید واژه : جدول زمانبندی دروس دانشگاهی، الگوریتم¬های خوشه¬بندی، الگوریتم مقایسه¬ی تصمیم گیری چند معیاره¬ی فازی و الگوریتم ترکیبی.
  •   Title : A New Approach to Solve University Course Timetabling Problem
  •   Abstract :
    University Course Time-Tabling Problem is a process of scheduling university courses for one semester by the faculties of a university, which is inherently NP-Complete problem. The main technique in the presented approach is focused on developing and making the process of timetabling common lecturers among different departments of a university scalable. This problem schedules and allocates events (lecturers/ students/ courses) to resources (time slots/ classrooms), which has two sensitive constraints including hard and soft constraints. The goal is to improve soft constraints. In this paper, the studied approaches include clustering algorithms (K-means, fuzzy C-means, and funnel), fuzzy multi-criteria decision making comparison, hybrid (local search/ genetic) and combination of clustering algorithms with fuzzy multi-criteria decision making comparison. For this, the optimization and performance comparisons of the algorithms used in this paper are thoroughly analyzed. Paper’s aims: 1) descending satisfaction of preferences and soft constraints of common lecturers among departments, 2) minimizing the loss of extra resources of each faculty. An applied dataset is based on meeting the requirements of scheduling in real world, among various departments of Islamic Azad University, Ahar Branch and the success of the results would be in respect of satisfying uniform distribution and allocation of common lecturers on extra resources among different departments.
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