Title: Multi-objective perishable multi-item green inventory models with uncertain finite time horizons and constraints by neutrosophic optimisation approach

Authors: Chaitali Kar; Manoranjan De; Manoranjan Maiti; Pritha Das

Addresses: Department of Mathematics, Indian Institute of Engineering Science and Technology, Howrah-711103, West Bengal, India ' Department of Mathematics, Mugberia Gangadhar Mahavidyalaya, Purba Medinipur-721425, West Bengal, India ' Department of Applied Mathematics, Vidyasagar University, Paschim Medinipur-721102, West Bengal, India ' Department of Mathematics, Indian Institute of Engineering Science and Technology, Howrah-711103, West Bengal, India

Abstract: The business period of seasonal products, such as mango, broccoli, etc., is finite over the years due to their availability, which is again uncertain for seasonal variations. According to FAO, about 40% of India's fruits and vegetables perish before reaching consumers. Due to global warming, firms have incorporated carbon management into business decisions. The resources in business are always limited and uncertain. Considering these facts, multi-objective perishable multi-product EOQ models with stock-dependent demand are formulated under crisp, uncertain (fuzzy, random, rough and neutrosophic) time horizons and constraints. The objective is to maximise total profit while minimising wastage costs and carbon emissions. Proposed models are solved using neutrosophic optimisation approach. The multi-objective problems are transformed into single ones using the weighted-sum method and solved through GRG (LINGO 11.0) method. Models are illustrated with numerical examples, and some sensitivity analyses are presented. A trade-off between profit and carbon emission is depicted.

Keywords: inventory; seasonal products; uncertain time horizon; carbon emission; neutrosophic optimisation.

DOI: 10.1504/IJMOR.2024.137053

International Journal of Mathematics in Operational Research, 2024 Vol.27 No.2, pp.167 - 198

Received: 13 Sep 2022
Accepted: 07 Jan 2023
Published online: 01 Mar 2024 *

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