Title
Razvoj modela za optimalno planiranje i raspoređivanje resursa u malim i srednjim preduzećima u uslovima neizvesnosti
Creator
Stanković, Aleksandar G., 1992-
CONOR:
131271433
Copyright date
2025
Object Links
Select license
Autorstvo-Nekomercijalno-Bez prerade 3.0 Srbija (CC BY-NC-ND 3.0)
License description
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Language
Serbian
Cobiss-ID
Theses Type
Doktorska disertacija
description
Datum odbrane: 08.10.2025.
Other responsibilities
Academic Expertise
Tehničko-tehnološke nauke
University
Univerzitet u Nišu
Faculty
Mašinski fakultet
Group
Katedra za transportnu tehniku i logistiku
Alternative title
Development of models for optimal resource planning and scheduling in small and medium-sized enterprises under conditions of uncertainty
Publisher
[A. G. Stanković]
Format
242 str.
description
Biografija autora: str. 238.
Bibliografija: str.207-226.
description
Transport technics and logistics
Abstract (en)
Manufacturing companies, particularly small and SMEs, are currently facing a range
of challenges in the industry, including shifts in product variety and production volume.
In order to effectively respond to these challenges, companies must adopt more flexible
and faster approaches. As the market continues to evolve, maintaining a high level of
competitiveness is essential for survival. The subject of the scientific research in this
doctoral dissertation is the development of a model for optimal planning and
scheduling of resources in SMEs under conditions of uncertainty. One of the key
research directions involves identifying the problems and challenges that SMEs in the
Republic of Serbia face in the process of resource management. Another research
direction focuses on examining and selecting the methods necessary for the design and
development of the optimization model. Special attention will be given to optimization
techniques and their integration with tools from probability theory, fuzzy logic, and
machine learning models. The third and fourth research directions concern the
development of the computational model itself and a hybrid approach that aims to
integrate multiple scientific methodologies into a unified planning system. This system
will enable the definition of an optimal production program in the form of a schedule
and resource allocation plan.The fifth research direction is the development of a
software application that translates complex algorithms and mathematical models into
intuitive, user-friendly interfaces. This application will allow production managers and
planners to easily input data, initiate optimization processes, and analyze results
without requiring deep technical expertise.
Authors Key words
planiranje i raspoređivanje resursa, razvoj modela i optimizacija proizvodnog
procesa, podrška malim i srednjim preduzećima u Republici Srbiji, veštačka
inteligencija, fazi logika, teorija verovatnoće i uslovi neizvesnosti
Authors Key words
planning and scheduling of resources, development of models and optimization
of the production process, support for small and medium-sized enterprises in the
Republic of Serbia, artificial intelligence and, conditions of uncertainty
Classification
334.713:005.591.1]:004.42(497.11)(043.3)
Subject
T120; P160; T260
Type
Tekst
Abstract (en)
Manufacturing companies, particularly small and SMEs, are currently facing a range
of challenges in the industry, including shifts in product variety and production volume.
In order to effectively respond to these challenges, companies must adopt more flexible
and faster approaches. As the market continues to evolve, maintaining a high level of
competitiveness is essential for survival. The subject of the scientific research in this
doctoral dissertation is the development of a model for optimal planning and
scheduling of resources in SMEs under conditions of uncertainty. One of the key
research directions involves identifying the problems and challenges that SMEs in the
Republic of Serbia face in the process of resource management. Another research
direction focuses on examining and selecting the methods necessary for the design and
development of the optimization model. Special attention will be given to optimization
techniques and their integration with tools from probability theory, fuzzy logic, and
machine learning models. The third and fourth research directions concern the
development of the computational model itself and a hybrid approach that aims to
integrate multiple scientific methodologies into a unified planning system. This system
will enable the definition of an optimal production program in the form of a schedule
and resource allocation plan.The fifth research direction is the development of a
software application that translates complex algorithms and mathematical models into
intuitive, user-friendly interfaces. This application will allow production managers and
planners to easily input data, initiate optimization processes, and analyze results
without requiring deep technical expertise.
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