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Title:Metode reševanja problemov mehkega linearnega programiranja
Authors:ID Žulj, Maja (Author)
ID Bokal, Drago (Mentor) More about this mentor... New window
Files:.pdf MAG_Repnik_Maja_2016.pdf (721,28 KB)
MD5: 91971DE518B266118C232DE48194977D
 
Language:Slovenian
Work type:Master's thesis
Typology:2.09 - Master's Thesis
Organization:FNM - Faculty of Natural Sciences and Mathematics
Abstract:V delu so obravnavane različne metode za reševanje problemov linearnega programiranja, kjer nastopajo nenatančne vrednosti, ki jih opišemo kot mehka števila. Najprej so vpeljani osnovni pojmi teorije mehkih množic in linearnega programiranja ter nekatere razširitve te tehnike. V delu ugotavljamo, da se je v literaturi pojavilo veliko modelov mehkih linearnih programov in posledično tudi veliko različnih metod, ki te probleme rešujejo. Navedenih je nekaj del, v katerih so avtorji razvrstili obstoječe metode po določenih kriterijih. Predstavljena je tudi tabela dimenzij, ki je osnova za taksonomijo, ki vključuje tudi novejše metode, ki še niso bile zbrane in popisane. Prav tako so predstavljeni problemi iz resničnega življenja, ki so rešeni z uporabo metod mehkega linearnega programiranja. V tretjem in četrtem poglavju je mehki linearni program razdeljen v skupine glede na to, v katerem delu nastopajo mehki koeficienti. Za vsako skupino je opisanih nekaj najpomembnejših metod. V zadnjem poglavju je izpostavljen problem pomanjkanja učinkovite programske opreme, ki preprečuje pogostejšo uporabo mehkega linearnega programiranja.
Keywords:mehke množice, primerjanje mehkih števil, linearno programiranje, večkriterijsko linearno programiranje, FuzzyLP.
Place of publishing:Maribor
Publisher:[M. Repnik]
Year of publishing:2016
PID:20.500.12556/DKUM-58668 New window
UDC:519.816:005.31(043.2)
COBISS.SI-ID:22534664 New window
NUK URN:URN:SI:UM:DK:KRLSW7TS
Publication date in DKUM:16.09.2016
Views:2045
Downloads:182
Metadata:XML DC-XML DC-RDF
Categories:FNM
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Secondary language

Language:English
Title:Methods for solving fuzzy linear programming problems
Abstract:In this thesis, we present various methods for solving linear programming problems with imprecise values, that are modelled as fuzzy numbers. First we introduce the basis of fuzzy sets and linear programming problems with some extensions. During our research, we noticed that many different models of fuzzy linear programming problems and consequently also methods to solve this problems appeared in literature. We present some existing classification of methods. We also made a table with dimensions, that can be a basis for taxonomy that include also recent methods, which can not be found in any published taxonomy. There are examples of real life problems, that are solved by fuzzy linear programming techniques. In third and fourth chapter, fuzzy linear programming problems are divided according to type, and for each type, we describe some of the most relevant methods. In the last chapter, we expose the lack of effective software, which is probably the reason that fuzzy linear programming methods are not used more widely in real life problems.
Keywords:fuzzy sets, fuzzy number comparison, linear programming, multi-objective linear programming, FuzzyLP


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