A multi-objective transportation problem under quantity dependent credit period and cost structure policies in triangular intuitionistic fuzzy environment

Bera, Raj Kumar; Mondal, Shyamal Kumar

doi:10.1016/j.engappai.2023.106396

Cited by 8 publications

(1 citation statement)

References 38 publications

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“…The approach to the modeling of the processes of manufacturing of petroleum refining products by the use of generalized nets (GN) is original and all publications to date are the work of the authors. To the extent that the GN is a process description tool with at least as much power as the Turing machine, it can describe processes in more detail than Petri nets, which are discussed, for example, in the works of Wu et al [30][31][32][33][34][35] and Zhang et al [36], as well as many other tools for modeling real-world processes, e.g., linear programming [37,38], transportation problems [39][40][41], neural networks [42][43][44], etc. For each of these, it is shown that their functions and results of their work are representable by a GN [45][46][47].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Production Process of Fuel Gas, LPG, Propylene, and Polypropylene in a Petroleum Refinery Using Generalized Nets

Stratiev,

Dimitriev,

Stratiev

et al. 2023

Mathematics

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The parallel processes involved in the production of refinery fuel gas, liquid petroleum gas (LPG), propylene, and polypropylene, occurring in thirteen refinery units, are modeled by the use of a Generalized Net (GN) apparatus. The modeling of the production of these products is important because they affect the energy balance of petroleum refinery and the associated emissions of greenhouse gases. For the first time, such a model is proposed and it is a continuation of the investigations of refinery process modelling by GNs. The model contains 17 transitions, 55 places, and 47 types of tokens, and considers the orders of fuel gas for the refinery power station, refinery process furnaces, LPG, liquid propylene, and 6 grades of polypropylene. This model is intended to be used as a more detailed lower-level GN model in a higher-level GN model that facilitates and optimizes the process of decision making in the petroleum refining industry.

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