Sustainable inventory management based on environmental policies for the perishable products under first or last in and first out policy

Vikash Murmu; Dinesh Kumar; Biswajit Sarkar; Rahul S Mor; Ashok Kumar Jha

doi:10.3934/jimo.2022149

Article Contents

2023, Volume 19, Issue 7: 4764-4803. Doi: 10.3934/jimo.2022149

This issue Previous Article Dual-channel supply chain coordination strategies considering electricity quality Next Article Retailing and servicing strategies for an imperfect production with variable lead time and backorder under online-to-offline environment

Sustainable inventory management based on environmental policies for the perishable products under first or last in and first out policy

1.
Dept. of Production & Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand - 831014, India
2.
Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
3.
Center for Transdisciplinary Research (CFTR), Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, 162, Poonamallee High Road, Velappanchavadi, Chennai, Tamil Nadu 600077, India
4.
Dept. of Food Engineering, National Institute of Food Technology Entrepreneurship and Management, Sonepat - 131028, India

^*Corresponding author: Biswajit Sarkar (Email: bsbiswajitsarkar@gmail.com)
^*Corresponding author: Biswajit Sarkar (Email: bsbiswajitsarkar@gmail.com)

Received: November 2021

Revised: May 2022

Early access: August 2022

Published: July 2023

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Abstract

Holistic, quality, and sustainability-based inventory policy for perishable items may prove to be a game-changer amid great concern over the carbon footprint and global economic crises. In this paper, first-in-first-out (FIFO) and last-in-first-out (LIFO) dispatching policies have been used to examine the effect of quality on fresh products' sales mind the sustainability concern. The quality of these products worsens with age. Its deterioration rate follows two parameters, Weibull distribution, as it gives better flexibility for various items subjected to deterioration and demonstrates fitness for a range of shape and scale parameters. An adequate preservation effort such as controlled atmosphere (CA) storage and modified atmosphere packaging (MAP) techniques must be applied during storage and handling to maintain such products' quality. Consumers' purchasing behavior and curiosity towards quality and selling price drive these products' demand variability. The demand has been considered a function of quality and unit selling price of the item. The effect of inflation viz. time value of money has also been taken into account, affecting Authoritarian governments' norms on carbon emission control in taxation have also been considered essential for modern sustainable inventory policies. The present models determine the unit price and lot size for the maximum average profit of the system. The behaviors of models have been investigated using a comprehensive sensitivity analysis that offers important operative implications. It has been found that the first-in-first-out model is more profitable as compared to the last-in-first-out model, the price is very rigid, and little flexibility in price drastically decreases the profit. Backlogging has no impact on the selling price of products and order quantity but reduces the average yield because of carbon emission taxation.

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Mathematics Subject Classification: Primary: 90B06, 90B50, 90B60; Secondary: 90C11, 90C31.

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Figure 1. Two warehouse inventory depletion with FIFO distribution strategy

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Figure 2. Average profit versus price per unit

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Figure 3. Average profit versus the number of items in system and price per unit

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Figure 4. Two warehouse inventory depictions with LIFO distribution strategy

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Figure 5. Number of items in the system versus price per unit

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Figure 6. Average profit versus the Number of items in the system and Price per unit

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Figure 7. Average profit versus the Number of items in the system and Price per unit

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Figure 8. (ⅰ-ⅴ): Variation of average profit (AP) for FIFO and LIFO concerning, (ⅰ) holding costs in RW,(ⅱ) price elasticity(ⅲ) backlogging parameter(ⅳ) quality parameter, and (ⅴ) fraction of carbon emission

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Table 2. Effect of holding costs in rented and owned warehouse in policy selection

M	N	P	$ G_F $	$ U_F $	AP (FIFO)	P	$ G_L $	$ U_L $	AP (LIFO)	Policy selected
1	1	105	200	188.50	1026.4	46.03	182	212.35	553.57	FIFO
	2	105	200	188.50	818.44	46.03	182	212.35	537.66	FIFO
	3	105	182	177.04	631.97	46.03	182	212.35	521.75	FIFO
2	1	105	200	188.50	988.41	55.34	182	197.15	521.60	FIFO
	2	105	200	188.50	780.44	52.34	182	197.15	498.27	FIFO
	3	105	182	171.04	593.97	52.24	182	201.17	475.64	FIFO
3	1	105	200	188.50	950.41	64.65	182	188.91	483.89	FIFO
	2	105	200	188.50	742.45	64.65	182	188.91	455.60	FIFO
	3	105	182	171.04	555.97	64.65	182	188.91	427.31	FIFO

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Table 3. Effect different values of demand parameters in policy selection

Z	n	p	$ G_F $	$ U_F $	AP (FIFO)	p	$ G_L $	$ U_L $	AP (LIFO)	Policy selected
100000	1.87	55.44	182	205.67	1539.1	52.24	182	251.43	1649.0	LIFO
	2	105	200	188.50	1026.4	46.03	182	212.35	537.66	FIFO
	2.2	105	200	189.10	8892.3	105	200	192.11	184.41	FIFO
200000	1.8	55.34	182	278.90	3541.7	49.12	182	380.88	3780.9	LIFO
	2	55.34	182	211.69	1343.3	46.03	182	268.11	1478.2	LIFO
	2.2	105	200	188.50	1328.4	46.03	182	208.77	488.11	FIFO
300000	1.8	52.24	182	379.36	5622.6	49.13	182	506.11	5967.8	LIFO
	2	49.13	182	257.98	2249.0	46.03	182	328.77	2459.0	LIFO
	2.2	105	200	188.65	947.63	42.93	182	246.48	910.45	FIFO

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Table 4. Effect of different values of the backlogging parameter in policy selection

$ \sigma $	p	$ G_F $	$ U_F $	AP (FIFO)	p	$ G_L $	$ U_L $	AP (LIFO)	Policy selected
0.7	61.55	182	177.54	552.62	49.13	182	266.14	526.82	FIFO
0.6	105	182	171.04	561.69	49.13	182	206.14	530.56	FIFO
0.4	105	200	188.50	766.03	49.13	182	206.14	537.04	FIFO
0.3	105	200	188.50	863.29	49.13	182	206.14	540.08	FIFO
0.2	105	200	188.50	949.00	46.03	182	212.35	544.60	FIFO

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Table 5. Effects quality parameter on policy selection

$ \beta $	p	$ G_F $	$ U_F $	AP (FIFO)	p	$ G_L $	$ U_L $	AP (LIFO)	Policy selected
5	105	200	188.50	1026.4	46.03	182	212.35	537.66	FIFO
15	105	200	193.94	640.93	42.93	182	222.22	401.90	FIFO
25	49.13	182	193.73	265.37	42.93	182	224.12	261.38	FIFO
35	42.93	182	206.68	132.07	36.72	182	250.22	125.98	FIFO
45	39.82	182	217.51	3.96	36.72	182	252.62	-1.08	FIFO

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Table 6. Effect of fractions of carbon emission on policy selection

$\epsilon$	p	$G_F$	$U_F$	AP (FIFO)	p	$G_L$	$U_L$	AP (LIFO)	Policy selected
0.1	105	200	188.50	1035.2	49.13	182	206.14	477.31	FIFO
0.2	105	200	188.50	1026.4	46.03	182	212.35	553.57	FIFO
0.3	105	200	188.50	1017.7	46.03	182	212.35	640.00	FIFO
0.4	105	200	188.50	1008.50	42.93	182	220.20	743.98	FIFO

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