Egyptian Informatics Journal (Dec 2024)

Interval valued inventory model with different payment strategies for green products under interval valued Grey Wolf optimizer Algorithm fitness function

  • Subhash Chandra Das,
  • Md. Al-Amin Khan,
  • Ali Akbar Shaikh,
  • Adel Fahad Alrasheedi

Journal volume & issue
Vol. 28
p. 100561

Abstract

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Numerous studies have explored pricing and lot-sizing strategies for various payment methods, but most have focused primarily on the buyer’s perspective. This study, however, approaches these strategies from a different perspective, incorporating key and relevant factors often overlooked. The volume of sales increases when a seller accepts a buyer’s credit. However, it reduces sales volume when a seller requests a buyer make a payment in advance. To boost sales and profitability, a vendor occasionally provides a price reduction in exchange for a down payment. Demanding a down payment from a customer earns interest and carries without any risk of default. When a vendor offers customers the option to pay with credit, a higher delay payment period facility plan may boost sales volume, but it also increases the risk of default. To maximize profit per unit of time, the vendor aims to simultaneously determine the optimal selling price, replenishment schedule, and payment method. This is achieved by comparing and calculating the vendor’s profit per time unit for credit, cash, and advance payment options. This is done by comparing and calculating the seller’s profit for each piece of time for credit, cash, and advance payments. The following managerial impacts are highlighted by means of numerical analyses: (1) A particular payment type, among the three available options, yields the seller’s highest profit under certain conditions. (2) It is vitally crucial for a vendor to provide a price reduction if an advance payment is required. (3) Advance payment results in higher profit than delayed payment if sales volume does not significantly fall while switching from credit to advance payments, or vice versa. To solve the optimization problem, a popular metaheuristic algorithm (viz., Grey Wolf Optimizer) is used and finally performed a post optimality analysis for making a fruitful conclusion.

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