The Teaching-Learning-Based Optimization (TLBO) algorithm is a new meta-heuristic algorithm which recently received more attention in various fields of science. The TLBO algorithm divided into two phases: Teacher phase and student phase; In the first phase a teacher tries to teach the student to improve the class level, then in the second phase, students increase their level by interacting amon...

Distributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

In this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. In this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. To tackle the problem efficiently and effectively, an effici...

Computer-aided process planning (CAPP) is an essential component in linking computer-aided design (CAD) and computer-aided manufacturing (CAM). Operation sequencing in CAPP is an essential activity. Each sequence of production operations which is produced in a process plan cannot be the best possible sequence every time in a changing production environment. As the complexity of the product incr...

The problem of the distribution of dairy products, which is classified as a combinatorial optimization problem, cannot be solved in polynomial time. In this paper, an algorithm based on Ant Colony Hybrid meta-heuristic system and Geographic Information System (GIS) was used to find a near-optimal solution to this problem. Using the former method, the nearest neighbor heuristic algorithm was use...

Brain tumors are deadly but become deadliest because of delayed and inefficient diagnosis process. Large variations in tumor types also instigate additional complexity. Machine vision brain addresses the problem. This research’s objective was to develop a classification model based on machine techniques using Magnetic Resonance Imaging (MRI). For this purpose, novel hybrid-brain-tumor-classific...

background and purpose: consideringbackground and purpose: considering the importance and necessity of competency-based education at a global level and with respect to globalization and the requirement of minimum competencies in medical fields, medical education communities and organizations worldwide have tried to determine the competencies, present frameworks and education models to respond t...

Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...