12,318 research outputs found
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
Performance optimization of a leagility inspired supply chain model: a CFGTSA algorithm based approach
Lean and agile principles have attracted considerable interest in the past few decades. Industrial sectors throughout the world are upgrading to these principles to enhance their performance, since they have been proven to be efficient in handling supply chains. However, the present market trend demands a more robust strategy incorporating the salient features of both lean and agile principles. Inspired by these, the leagility principle has emerged, encapsulating both lean and agile features. The present work proposes a leagile supply chain based model for manufacturing industries. The paper emphasizes the various aspects of leagile supply chain modeling and implementation and proposes a new Hybrid Chaos-based Fast Genetic Tabu Simulated Annealing (CFGTSA) algorithm to solve the complex scheduling problem prevailing in the leagile environment. The proposed CFGTSA algorithm is compared with the GA, SA, TS and Hybrid Tabu SA algorithms to demonstrate its efficacy in handling complex scheduling problems
Current Trends in Simheuristics: from smart transportation to agent-based simheuristics
Simheuristics extend metaheuristics by adding a
simulation layer that allows the optimization component to deal
efficiently with scenarios under uncertainty. This presentation
reviews both initial as well as recent applications of simheuristics,
mainly in the area of logistics and transportation. We also discuss
a novel agent-based simheuristic (ABSH) approach that combines simheuristic and multi-agent systems to efficiently solve stochastic combinatorial optimization problems. The presentation is based on papers [1], [2], and [3], which have been already accepted in the prestigious Winter Simulation Conference.Peer ReviewedPostprint (published version
Engineering calculations for communications systems planning
The single entry interference problem is treated for frequency sharing between the broadcasting satellite and intersatellite services near 23 GHz. It is recommended that very long (more than 120 longitude difference) intersatellite hops be relegated to the unshared portion of the band. When this is done, it is found that suitable orbit assignments can be determined easily with the aid of a set of universal curves. An attempt to develop synthesis procedures for optimally assigning frequencies and orbital slots for the broadcasting satellite service in region 2 was initiated. Several discrete programming and continuous optimization techniques are discussed
AN INVESTIGATION INTO AN EXPERT SYSTEM FOR TELECOMMUNICATION NETWORK DESIGN
Many telephone companies, especially in Eastern-Europe and the 'third world', are
developing new telephone networks. In such situations the network design engineer needs
computer based tools that not only supplement his own knowledge but also help him to cope
with situations where not all the information necessary for the design is available. Often
traditional network design tools are somewhat removed from the practical world for which
they were developed. They often ignore the significant uncertain and statistical nature of the
input data. They use data taken from a fixed point in time to solve a time variable problem,
and the cost formulae tend to be on an average per line or port rather than the specific case.
Indeed, data is often not available or just plainly unreliable. The engineer has to rely on
rules of thumb honed over many years of experience in designing networks and be able to
cope with missing data.
The complexity of telecommunication networks and the rarity of specialists in this area often
makes the network design process very difficult for a company. It is therefore an important
area for the application of expert systems. Designs resulting from the use of expert systems
will have a measure of uncertainty in their solution and adequate account must be made of
the risk involved in implementing its design recommendations.
The thesis reviews the status of expert systems as used for telecommunication network
design. It further shows that such an expert system needs to reduce a large network problem
into its component parts, use different modules to solve them and then combine these results
to create a total solution. It shows how the various sub-division problems are integrated to
solve the general network design problem. This thesis further presents details of such an
expert system and the databases necessary for network design: three new algorithms are
invented for traffic analysis, node locations and network design and these produce results
that have close correlation with designs taken from BT Consultancy archives.
It was initially supposed that an efficient combination of existing techniques for dealing with uncertainty
within expert systems would suffice for the basis of the new system. It soon
became apparent, however, that to allow for the differing attributes of facts, rules and data
and the varying degrees of importance or rank within each area, a new and radically different
method would be needed.
Having investigated the existing uncertainty problem it is believed that a new more rational
method has been found. The work has involved the invention of the 'Uncertainty Window'
technique and its testing on various aspects of network design, including demand forecast,
network dimensioning, node and link system sizing, etc. using a selection of networks that
have been designed by BT Consultancy staff. From the results of the analysis, modifications
to the technique have been incorporated with the aim of optimising the heuristics and
procedures, so that the structure gives an accurate solution as early as possible.
The essence of the process is one of associating the uncertainty windows with their relevant
rules, data and facts, which results in providing the network designer with an insight into the
uncertainties that have helped produce the overall system design: it indicates which sources
of uncertainty and which assumptions are were critical for further investigation to improve
upon the confidence of the overall design. The windowing technique works by virtue of its
ability to retain the composition of the uncertainty and its associated values, assumption, etc.
and allows for better solutions to be attained.BRITISH TELECOMMUNICATIONS PL
Application of artificial neural network in market segmentation: A review on recent trends
Despite the significance of Artificial Neural Network (ANN) algorithm to
market segmentation, there is a need of a comprehensive literature review and a
classification system for it towards identification of future trend of market
segmentation research. The present work is the first identifiable academic
literature review of the application of neural network based techniques to
segmentation. Our study has provided an academic database of literature between
the periods of 2000-2010 and proposed a classification scheme for the articles.
One thousands (1000) articles have been identified, and around 100 relevant
selected articles have been subsequently reviewed and classified based on the
major focus of each paper. Findings of this study indicated that the research
area of ANN based applications are receiving most research attention and self
organizing map based applications are second in position to be used in
segmentation. The commonly used models for market segmentation are data mining,
intelligent system etc. Our analysis furnishes a roadmap to guide future
research and aid knowledge accretion and establishment pertaining to the
application of ANN based techniques in market segmentation. Thus the present
work will significantly contribute to both the industry and academic research
in business and marketing as a sustainable valuable knowledge source of market
segmentation with the future trend of ANN application in segmentation.Comment: 24 pages, 7 figures,3 Table
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