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Title:Koordinacija blagovnega toka v maloprodajni oskrbovalni verigi
Authors:Vizinger, Tea (Author)
Žerovnik, Janez (Mentor) More about this mentor... New window
Kramberger, Tomaž (Co-mentor)
Files:.pdf DOK_Vizinger_Tea_2019.pdf (3,80 MB)
MD5: 43C5294A3069DAF403E01EF45880E137
 
Language:Slovenian
Work type:Dissertation (m)
Typology:2.08 - Doctoral Dissertation
Organization:FL - Faculty of Logistic
Abstract:Disertacija obravnava koordinacijo blagovnih tokov v maloprodajnih oziroma trgovinskih oskrbovalnih verigah. Zanje je značilno, da delujejo v nenehno spreminjajočem se okolju ter so močno odvisne od povpraševanja končnih odjemalcev. Tipično maloprodajno oskrbovalno verigo sestavlja več trgovin, ki so oskrbovane iz vsaj enega skladišča izbranega trgovca. Da dosežemo usklajenost zalog med objekti dane oskrbovalne verige, je zagotovo najprej potrebno doseči primerno koordinacijo vseh povezanih in odvisnih si aktivnosti, ki spremljajo blagovni tok. Pri gradnji matematičnega modela smo se najprej osredotočili na analizo povpraševanja, medtem ko so dinamično prilagajanje cen, upoštevanje pokvarljivosti itd. predmet nadaljnih raziskav, povezanih s komplementarnim modelom za operativno planiranje blagovnega toka. Idejno je pristop zasnovan tako, da se najprej poišče primerni distribucijski plan (taktični plan) z minimalnimi pričakovanimi stroški distribucije, kot tudi z minimalnimi pričakovanimi stroški rizikov. Problem predstavljamo kot večkriterijski problem optimizacije, predlagani stohastični model za dosego koordinacije pa pri tem kombinira več metod in postopkov iz področij teorije grafov, teorije verjetnosti in operacijskih raziskav. Ker je izbrani problem računsko kompleksen, za njegovo reševanje uporabimo nekaj hevrističnih postopkov lokalnega iskanja ter tudi predlagamo robustni optimizacijski pristop reševanja danega problema. Eksperimentalna študija pokaže, da je za optimizacijski problem mogoče implementirati algoritem, ki da uporabne rešitve.
Keywords:Distribucija, Zaloge, Optimizacija, Hevristike, Stohastično programiranje
Year of publishing:2019
Publisher:[T. Vizinger]
Source:Celje
UDC:658.7
COBISS_ID:513032509 New window
NUK URN:URN:SI:UM:DK:FLRU0TFG
Views:566
Downloads:84
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Categories:FL
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:10.05.2019

Secondary language

Language:English
Title:Coordination of a retail supply chain product flow
Abstract:The thesis deals with the coordination of product flows in the retail supply chain. Supply chains operate in a constantly changing environment and strongly depend on consumer demands. A typical retail supply chain consists of several stores that are supplied from at least one retailer’s warehouse. In order to achieve consistent supplies between supply chain facilities, it is urgent to first achieve a proper coordination of the interrelated activities. When defining a mathematical model, our first focus was on future demand satisfaction, whereas pricing policies, perishability and other factors will be addressed by further research on the complementary model for the operative planning. The idea is to first obtain a preferable distribution plan (tactical plan) with minimal expected distribution costs and minimal expected supply risks. The problem is presented as a multi-objective optimization problem, for which we propose the stochastic model that combines several methods and procedures, including graph theory, probability theory and operational research. As the selected problem is computationally hard to solve, we use local search heuristics and propose a robust optimization solution approach. The experimental study shows that for the optimization problem we can implement an algorithm that provides useful solutions.
Keywords:Distribution, Inventory, Optimization, Heuristics, Stochastic programming


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