Task scheduling plays an important part in the improvement of parallel and distributed systems. The problem of task scheduling has been shown to be NP hard. The time consuming is more to solve the problem in deterministic techniques. There are algorithms developed to schedule tasks for distributed environment, which focus on single objective. The problem becomes more complex, while considering ...

In Multi-objective Optimization the goal is to present a set of Pareto-optimal solutions to the decision maker (DM). One out of these solutions is then chosen according to the DM preferences. Given that the DM has some general idea of what type of solution is preferred, a more efficient optimization could be run. This can be accomplished by letting the optimization algorithm make use of this pr...

Market-oriented production systems generally have the characteristics of multi-product and small-batch production. Dynamic virtual cellular manufacturing create cells periodically in a planning horizon to respond changing demands flexibly quickly, thus are suitable for problems market-oriented systems. In current research, we propose dynamic cell reconfiguration framework under environment with...

A metaheuristic approach for variable axial composites considering multiobjective optimization is investigated. The proposed methodology based on the combination of three main parts: a defining orientation fibers in laminate, structural analysis program (based Finite Element Method) and an algorithm. It important to highlight that radial basis function (RBF), which describes smooth fiber patter...

Nowadays, the capability of cloud management suppliers is one of the important advantages for suppliers that can improve the performance and flexibility and reduce costs in companies through easy access to resources. Also, the environmental impacts of suppliers are a significant issue in today’s industrialization and globalization world. This paper analyzes these subjects by fuzzy multi-objecti...

In this paper, we apply an elitist multi-objective genetic algorithm for solving mechanical component design problems with multiple objectives. Although there exists a number of classical techniques, evolutionary algorithms (EAs) have an edge over the classical methods in that they can find multiple Pareto-optimal solutions in one single simulation run. The proposed algorithm (we call NSGA-II) ...

in the new production systems, finding a way to improving the product and system reliability in design is a very important. the reliability of the products and systems may improve using different methods. one of this methods is redundancy allocation problem. in this problem by adding redundant component to sub-systems under some constraints, the reliability improved. in this paper we worked on ...

Modern this paper proposes non dominated sorting genetic algorithm (NSGA-II) which has feature of adaptive crowding distance for finding optimal location and sizing of Static Var Compensators (SVC) in order to minimize real power losses and voltage deviation and also to improve voltage profile of a power system at the same time. While finding the optimal location and size of SVC, single line ou...

The design of an urban water distribution system (WDS) is a challenging problem involving multiple objectives. The goal of robust multi-objective optimization for WDS design is to find the set of solutions which embodies an acceptable trade-off between system cost and reliability, so that the ideal solution may be selected for a given budget. In addition to satisfying consumer needs, a system m...