A multi-objective transportation problem with cost dependent credit period policy under Gaussian fuzzy environment

In the recent competitive market of transportation business, it is becoming increasingly difficult to improve the facilities for retailer services. Recently, several kinds of policies are being adopted by different distributors to provide their best services in favor of retailers. One of these is the advantage in credit period policy which increases the period between the receipt of items and the payment due date. Because of this policy, due to the late payment, certain interest for the payable amount is credited to whom the credit period is offered. From this perspective, a multi-objective transportation problem has been formulated under cost-dependent credit period policy. Here, the items are transported from a production house to the retailers by distributors who act as mediators. For adequate uncertainty in the cost parameter, it is considered as Gaussian fuzzy number. The key objective of this research is to maximize the profit of the distributors and to minimize the cost of the retailers simultaneously under a credit period policy in Gaussian fuzzy environment. Considering all the aspects, four models are constructed and illustrated mathematically and numerically. The effect of fuzziness on the model solution has been analyzed in detail; how distributors can improve their profit structure and retailers can reduce their cost structure under the used cost dependent credit period policy is also discussed. Finally, we have figured out some managerial insights and mentioned future research scope.