Two-plant production model with customers’ demand dependent on warranty period of the product and carbon emission level of the manufacturer via different meta-heuristic algorithms

In the developed countries, most of the customers are aware about the harmful effects of purchased products that pollute the environment. On the other hand, the aim of the manufacturer is to reduce by controlling the pollution rates. Motivating from this situation, a two-plant production model in si...

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Published inNeural computing & applications Vol. 33; no. 21; pp. 14263 - 14281
Main Authors Manna, Amalesh Kumar, Benerjee, Tanmoy, Mondal, Sankar Prasad, Shaikh, Ali Akbar, Bhunia, Asoke Kumar
Format Journal Article
LanguageEnglish
Published London Springer London 01.11.2021
Springer Nature B.V
Subjects
Online AccessGet full text
ISSN0941-0643
1433-3058
DOI10.1007/s00521-021-06073-9

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Abstract In the developed countries, most of the customers are aware about the harmful effects of purchased products that pollute the environment. On the other hand, the aim of the manufacturer is to reduce by controlling the pollution rates. Motivating from this situation, a two-plant production model in single manufacturing system with warranty period of the product and carbon emission level dependent demand is developed. The manufacturer inspects every produced item in both plants before sending it to the market. After inspection, a part of imperfect items is reworked to reproduce these items into perfect items and also to reduce the loss of the manufacturer. The objective of the model is to determine the optimal values of the product’s warranty period and the production period in each plant in order to maximize the average profit of the manufacturer subject to some constraints. To illustrate and validate the model, two numerical examples are considered and solved by four meta-heuristic algorithms. Finally, to examine the effects of some significant model parameters on the optimal policy, sensitivity analyses are performed.
AbstractList In the developed countries, most of the customers are aware about the harmful effects of purchased products that pollute the environment. On the other hand, the aim of the manufacturer is to reduce by controlling the pollution rates. Motivating from this situation, a two-plant production model in single manufacturing system with warranty period of the product and carbon emission level dependent demand is developed. The manufacturer inspects every produced item in both plants before sending it to the market. After inspection, a part of imperfect items is reworked to reproduce these items into perfect items and also to reduce the loss of the manufacturer. The objective of the model is to determine the optimal values of the product’s warranty period and the production period in each plant in order to maximize the average profit of the manufacturer subject to some constraints. To illustrate and validate the model, two numerical examples are considered and solved by four meta-heuristic algorithms. Finally, to examine the effects of some significant model parameters on the optimal policy, sensitivity analyses are performed.
Author Benerjee, Tanmoy
Shaikh, Ali Akbar
Bhunia, Asoke Kumar
Manna, Amalesh Kumar
Mondal, Sankar Prasad
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  givenname: Ali Akbar
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  organization: Department of Mathematics, The University of Burdwan
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  organization: Department of Mathematics, The University of Burdwan
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Snippet In the developed countries, most of the customers are aware about the harmful effects of purchased products that pollute the environment. On the other hand,...
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SubjectTerms Algorithms
Artificial Intelligence
Carbon
Computational Biology/Bioinformatics
Computational Science and Engineering
Computer Science
Customers
Data Mining and Knowledge Discovery
Heuristic methods
Image Processing and Computer Vision
Inspection
Manufacturers
Original Article
Parameter sensitivity
Probability and Statistics in Computer Science
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Title Two-plant production model with customers’ demand dependent on warranty period of the product and carbon emission level of the manufacturer via different meta-heuristic algorithms
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