The Internet and the World Wide Web in particular provide a unique platform to connect learners with educational resources. Educational material in hypermedia formed in a Web-based educational system makes learning a task-driven process, motivating learners to explore alternative navigational paths through the domain knowledge and from different resources around the globe. Many researchers have focused on developing e-learning systems with personalized learning mechanisms to assist on-line Web-based learning and to adaptively provide learning paths. Although most personalized systems consider learner preferences, interests and browsing behaviors when providing personalized curriculum sequencing services, these systems usually neglect to consider whether learner ability and the difficulty level of the recommended curriculums are matched to each other. Therefore, the authors proposed approach is based on an integer program (IP) to optimize user curriculum accompanying with fuzzy logic approach which analyze the effective criteria by linguistic variables in a knowledge based system. The effectiveness of the proposed framework is shown by numerical illustrations which are inferenced from the designed user interface.

We concern with both time and cost optimization in an automated manufacturing system. In our proposed system, material handling is carried out by automated guided vehicles and robots for the manufacturing functions. In this way, defect rates, breakdown times, waiting time, processing time, and certain other parameters are not expected to be deterministic. Therefore, we apply stochastic programming to optimize the production time and material handling cost. The proposed stochastic program is a nonlinear model, for this reason we apply a successive linear programming (SLP) technique for its optimization. Numerical test results point to the inefficacy of the proposed optimization method for large sized problems. Hence, a genetic algorithm (GA) is presented to optimize large sized problems.