Neutrosophic trade-credit EOQ model for deteriorating items considering expiration date of the items using different variants of particle swarm optimizations

In reality, many businessmen often offer their products on delay or trade credit payments scheme to boost sales and diminish inventory. Trade credit financing plays a vital role in enabling retailers and customers to purchase goods without making prompt payments. As part of the trade credit financing scheme, the retailer receives an upstream trade credit from the supplier, while the retailer offers downstream trade credit to its customers. This paper proposes and explores an EOQ model involving an inventory-dependent demand and a trade credit scheme. In addition, expiration dates are taken into account when calculating the deterioration rate (e.g., various packaged food items, medicines, some cosmetic items etc.). As few parameters involve some sorts of uncertainty, we develop an imprecise and a crispified model in close parallel with the deterministic one. To represent this impreciseness in terms of linear trapezoidal neutrosophic fuzzy numbers (LTrNFN) as well as to crispify them, we use the removal area method. Then the crisp and crispified models are solved by using Weighted Quantum-Behaved Particle Swarm Optimization (WQPSO), Gaussian Quantum-Behaved Particle Swarm Optimization (GQPSO), and Adaptive Quantum-Behaved Particle Swarm Optimization (AQPSO), and the optimum profit is obtained from the best profit of these three algorithms. A number of numerical examples are presented in order to evaluate the validity of the proposed models and algorithms. Finally, the effects of changes of different inventory parameters involved in the crisp and crispified models are performed and some managerial insights are pointed out.