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http://hdl.handle.net/2080/1380
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DC Field | Value | Language |
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dc.contributor.author | Mishra, S K | - |
dc.contributor.author | Panda, G | - |
dc.contributor.author | Meher, S | - |
dc.contributor.author | Majhi, R | - |
dc.date.accessioned | 2011-02-05T06:26:12Z | - |
dc.date.available | 2011-02-05T06:26:12Z | - |
dc.date.issued | 2011-01 | - |
dc.identifier.citation | International Conference on Electronics Systems (ICES-2011),National Institute of Technology, Rourkela, India, 7-9th Jan 2011 | en |
dc.identifier.uri | http://hdl.handle.net/2080/1380 | - |
dc.description | Copyright belongs to proceeding publisher | en |
dc.description.abstract | The use of evolutionary algorithms in diversified application domains has gained ever increasing popularity in the last few years producing a wide range of interesting applications ranging from engineering and computer science to ecology, sociology and medicine. From these diversified application areas of evolutionary algorithms, economics and finance constitutes a very promising field.The use of evolutionary algorithms for solving multiobjective optimization problem emerges as a potential field of research in recent years. This paper presents the use of multi-objective evolutionary algorithms (MOEAs) for solving problems in economics and finance. Different applications of MOEA are explained briefly and a specific simulation work has been done for one particular application i.e. investment portfolio optimization. | en |
dc.format.extent | 234356 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | - |
dc.subject | Multi-objective optimization | en |
dc.subject | Paretooptimal solutions | en |
dc.subject | Global optimization | en |
dc.subject | Crowding distance | en |
dc.subject | Pareto front | en |
dc.title | A Study on Multi-Objective Evolutionary Algorithms and its Applications to Economics and Finance | en |
dc.type | Article | en |
Appears in Collections: | Conference Papers |
Files in This Item:
File | Description | Size | Format | |
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Multi objective.pdf | 228.86 kB | Adobe PDF | View/Open |
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