Particle Swarm Optimization (PSO) is a meta-heuristic algorithm that has been shown to be successful in solving a wide variety of real and complicated optimization problems in engineering and computer science. This paper introduces a projection based PSO technique, named ProjPSO, to efficiently find different types of optimal designs, or nearly optimal designs, for mixture models with and witho...

Feature selection is vital in the field of pattern classification due to accuracy and processing time considerations.The selection of proper features is of greater importance when the initial feature set is considerably large. Text classification is a typical example of this situation, where the size of the initial feature set may reach to hundreds or even thousands. There are numerous research...

Flow shop scheduling of jobs has always been a popular problem that has found solutions in the number of heuristic and meta-heuristic techniques. In this manuscript, two-machine flow shop scheduling problem has been investigated while optimizing makespan and idle time of machines. Uncertainties in the processing time and set up times of jobs involved are also taken into consideration in the for...

Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem. Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms. Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve differenttypes of NP-hard problems.However, ant colony s...