ماهنامه شباک
پیاپی 13 (شهریور 1395)

This paper presents multi-objective optimization model for designing a blood supply chain network under uncertainty by concentrating on locating and allocating different facilities in disaster. Some assumptions to have more accurate modelling of the real world is considered as follow: uncertainty of demand and donation, transshipment between different hospitals in order to address the demands and cope with the shortage, considering all of the blood products, temporary and permanent capacitated facilities and also considering two different objective functions (include time and cost objective functions). It should be noticed to emphasize the accessibility, disruption and also to cope with the uncertainty, the proposed model is considered in disaster. The model also utilized the ɛ-constraint and robust optimization method to solve the problem and is implemented on real data sets of Tehran and the previous studies of blood supply chain in Iran. At the end the performance of the proposed model is investigated.

For years, researchers tried to rehabilitation and construction of artificial organs, which reduces processing time to be appropriate for use in real time, however in these areas have been successful, but in most previous studies to detect the motion before observing was not concerned. It was Shown to help multi-objective optimization methods, can be contrasted between different objectives were to answer that in fact is a compromise between the various objective. The advantage of this method compared to simple objective methods can be used to identify a greater number of solutions, the ability to add different rules in the future and more realistic models of these issues can be mentioned.
The overall goal of this research is to provide a method for diagnosis of real-time movement in arm muscles based on EMG signal processing surface to control a cybernetic arm using appropriate time-frequency features multi-objective genetic algorithm NSGA-II selected by the As well as the use of support vector machine classifier to real-time motion detection is applied.
The results of processing 100 samples of recorded data from 5 healthy subjects indicated arm muscles that the proposed method can be used, with the optimal window mS256 and 98.43% with high accuracy, process, motion detection and diagnosis of arms used in three different modes. It can be claimed that the use of this method, to achieve optimization of error is less and also the convergence speed than previous methods.

Liquid rocket engine design, combustion due to high temperatures and high rates of heat transfer (1MW / m2 to about 160MW / m2) of hot gases to the chamber walls, the cooling thrust chamber of the utmost importance. The thrust chamber cooling design, selection of appropriate methods, design and related topics thrust chamber cooling ducts, double glazing and thermal coating is very important. Liquid propellant engine in the wall of the combustion chamber and nozzle is necessary in order to prevent the failure of a cooling system used engine block resistance. Cooling the refrigerant recovery method (usually fuel) through channels for which it is embedded in the engine block and passed through the engine block reduces the temperature. Modeling and analysis of fluid flow channels in the engine cooling liquid propellant because of the high heat flux one of the most important and most challenging issue in the context of this type of engine. That's why in this article cooling channel recovery numerical simulation is a liquid propellant engine. The engine is fed with cryogenic cooling and cryogenic propellant as the cooling fluid is intended.to increase or decrease the amount of flux is not.

In many cases, the issue of classification and rating the projects in project based organizations is great importance. In fact, rating and project selection means prioritization among some projects and allocating the resources between them in other to maximize the organizations profit. Some factors are involved in selection of the best layout of projects. Due to the fact that the degree of importance of criteria and satisfying the criteria are usually uncertain and ambiguous, in this study, by implementation of linguistic varuable and fuzzy set theory criteria are weighted and consequently using the fuzzy multi criteria decision making, the projects are rated and prioritized. This method was implemented in a project based company as a case study and using the its experts comments and Delphi fuzzy method project scores and criteria weight were collected. Then using the mentioned fuzzy method, rating and prioritization of the projects of this company is done.

Distribution System expansion Planning (DEP) is the most important factor in the demand growth in the system. Planning involves the installation of new facilities, including feeder and new routes. In this paper, a new method is proposed under load uncertainty to obtain the best feeder expansion scheme in different candidate. The objective function of proposed model is minimization of the total investment, operation, maintenance and line loss costs. Moreover, improve voltage profile and reduction of power losses are investigated. The proposed planning is optimized using the binary particle swarm optimization (BPSO) technique. In addition, the uncertainty is modeled using Monte-Carlo simulation (MCS). The simulation results prove the ability and effectiveness of the proposed planning method to deal with uncertainty and operating investment Process.