Telecommunications Network Planning and Maintenance

Telecommunications network operators are on a constant challenge to provide new services which require ubiquitous broadband access. In an attempt to do so, they are faced with many problems such as the network coverage or providing the guaranteed Quality of Service (QoS). Network planning is a multi-objective optimization problem which involves clustering the area of interest by minimizing a cost function which includes relevant parameters, such as installation cost, distance between user and base station, supported traffic, quality of received signal, etc. On the other hand, service assurance deals with the disorders that occur in hardware or software of the managed network. This paper presents a large number of multicriteria techniques that have been developed to deal with different kinds of problems regarding network planning and service assurance. The state of the art presented will help the reader to develop a broader understanding of the problems in the domain

Tokamak plasma boundary reconstruction using toroidal harmonics and an optimal control method

This paper proposes a new fast and stable algorithm for the reconstruction of the plasma boundary from discrete magnetic measurements taken at several locations surrounding the vacuum vessel. The resolution of this inverse problem takes two steps. In the first one we transform the set of measurements into Cauchy conditions on a fixed contour $\Gamma\_O$ close to the measurement points. This is done by least square fitting a truncated series of toroidal harmonic functions to the measurements. The second step consists in solving a Cauchy problem for the elliptic equation satisfied by the flux in the vacuum and for the overdetermined boundary conditions on $\Gamma\_O$ previously obtained with the help of toroidal harmonics. It is reformulated as an optimal control problem on a fixed annular domain of external boundary $\Gamma\_O$ and fictitious inner boundary $\Gamma\_I$. A regularized Kohn-Vogelius cost function depending on the value of the flux on $\Gamma\_I$ and measuring the discrepency between the solution to the equation satisfied by the flux obtained using Dirichlet conditions on $\Gamma\_O$ and the one obtained using Neumann conditions is minimized. The method presented here has led to the development of a software, called VacTH-KV, which enables plasma boundary reconstruction in any Tokamak.Comment: Fusion Science and Technology, 201

A mathematical model for the industrial hazardous waste location-routing problem

Technology progress is a cause of industrial hazardous wastes increasing in the whole world . Management of hazardous waste is a significant issue due to the imposed risk on environment and human life. This risk can be a result of location of undesirable facilities and also routing hazardous waste. In this paper a biobjective mixed integer programing model for location-routing industrial hazardous waste with two objectives is developed. First objective is total cost minimization including transportation cost, operation cost, initial investment cost, and cost saving from selling recycled waste. Second objective is minimization of transportation risk. Risk of population exposure within bandwidth along route is used to measure transportation risk. This model can help decision makers to locate treatment, recycling, and disposal centers simultaneously and also to route waste between these facilities considering risk and cost criteria. The results of the solved problem prove conflict between two objectives. Hence, it is possible to decrease the cost value by marginally increasing the transportation risk value and vice versa. A weighted sum method is utilized to combine two objectives function into one objective function. To solve the problem GAMS software with CPLEX solver is used. The problem is applied in Markazi province in Iran

Optimizing Effort and Time Parameters of COCOMO II Estimation using Fuzzy Multi-objective PSO

The  estimation  of  software  effort  is  an  essential and  crucial   activity   for  the  software   development   life  cycle. Software effort estimation is a challenge that often appears on the project of making a software. A poor estimate will produce result in a worse project management.  Various software cost estimation model has been introduced  to resolve this problem. Constructive Cost Model II (COCOMO II Model) create large extent most considerable  and broadly  used as model  for cost estimation.  To estimate   the  effort  and  the  development   time  of  a  software project,  COCOMO  II model uses cost drivers,  scale factors  and line  of  code.  However,  the  model  is  still  lacking  in  terms  of accuracy both in effort and development  time estimation.  In this study,   we   do   investigate   the   influence   of   components   and attributes to achieve new better accuracy improvement on COCOMO II model. And we introduced the use of Gaussian Membership  Function  (GMF)  Fuzzy  Logic  and Multi-Objective Particle Swarm Optimization method (MOPSO) algorithms in calibrating  and optimizing  the COCOMO  II model parameters. The   proposed   method   is   applied   on   Nasa93   dataset.   The experiment  result of proposed method able to reduce error down to  11.891%  and  8.082%  from  the  perspective  of  COCOMO  II model.  The  method  has  achieved  better  results  than  those  of previous   researches   and  deals  proficient   with  inexplicit   data input and further improve reliability of the estimation method