Application of artificial bee colony algorithm on a green production inventory problem with preservation for deteriorating items in neutrosophic fuzzy environment

Due to fluctuation of the market and several other reasons, most of the parameters related to the production inventory system, like, deterioration rate, demand rate and different costs are not always constants. These parameters involve some sorts of impreciseness which may be represented by stochast...

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Bibliographic Details
Published in:International journal of system assurance engineering and management 2024-02, Vol.15 (2), p.672-686
Main Authors: Supakar, Puja, Manna, Amalesh Kumar, Mahato, Sanat Kumar, Bhunia, Asoke Kumar
Format: Article
Language:English
Subjects:
Bees
Engineering
Engineering Economics
Fuzzy logic
Fuzzy sets
Inventory management
Logistics
Marketing
Mathematical models
Numerical models
Optimization algorithms
Organization
Original
Original Article
Parameters
Production costs
Quality Control
Reliability
Safety and Risk
Search algorithms
Swarm intelligence
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Summary:Due to fluctuation of the market and several other reasons, most of the parameters related to the production inventory system, like, deterioration rate, demand rate and different costs are not always constants. These parameters involve some sorts of impreciseness which may be represented by stochastic, fuzzy, fuzzy-stochastic, interval, intuitionistic fuzzy, neutrosophic fuzzy, etc. approaches. In this work, a green production model is formulated for deteriorating items in neutrosophic uncertain environment. In this proposed model, customers’ demand rates are influenced by their green level and the selling price of the manufacturing goods. Here, it is also considered that the deterioration rate is dependent on preservation investment whereas the production cost is dependent on the product’s green level. We have designed, analyzed, and solved the proposed model in crisp, neutrosophic and crispified forms. To illustrate this model numerically, two examples are constructed and solved by an artificial bee colony algorithm. Finally, sensitivity analyses are conducted graphically with respect to some of the system parameters involved in the crispified model.
ISSN:0975-6809
0976-4348
DOI:10.1007/s13198-022-01692-4