an alternative for decreasing risk for knowledge workers is effective & optimized work break.major performance criteria in r&d; based organization is successful projects. selection of opproporiate members can be a most effect on the projects achievement. but as the selection of r&d; special members lead to decrease of risk, repeatative participation of this people in the same project lead to kn...

....... The fast and elitist non-dominated sorting genetic algorithm (NSGA-II) contains a mechanism to sort individuals in a multi-objective optimization problem into non-dominated fronts, based on their performance in each optimization variable. When dealing with a bi-objective problem it is possible to carry-out the non-dominated sorting more efficiently, using the new sorting method presente...

In design and fabricate drive shafts with high value of fundamental natural frequency that represented high value of critical speed; using composite materials instead of typical metallic materials could provide longer length shafts with lighter weight. In this paper, multi-objective optimization (MOP) of a composite drive shaft is performed considering three conflicting objectives: fundamental ...

the vehicle driving comfort has become one of the important factors of vehicle quality and receives increasing attention. in this paper, optimal points of vehicle suspension parameters are generated using modified non-dominated sorting genetic algorithm (nsga-ii) for pareto optimization of 5-degree of freedom vehicle vibration model considering three conflicting functions simultaneously. in thi...

 In this research, a tri-objective mathematical model is proposed for the Transportation-Location-Routing problem. The model considers a three-echelon supply chain and aims to minimize total costs, maximize the minimum reliability of the traveled routes and establish a well-balanced set of routes. In order to solve the proposed model, four metaheuristic algorithms, including Multi-Objective Gre...

....... An important problem in the realm of evolutionary multi-objective optimization (MOO) is that of finding all non-dominated fronts (NDFs). We specifically address the computational efficiency of the non-dominated sorting algorithm for finding the non-dominated fronts for the non-dominated sorting genetic algorithm II (NSGA-II) algorithm. We introduce the Limiting Index Sort (LIS) algorith...