Abstract
Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. This paper presents a mathematical model for a three-level supply chain, which includes one producer, one distributor and one retailer. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The study is supported by several numerical examples and sensitivity analysis is performed to analyze the effects of the changes in different parameters on the optimal solution. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and also significantly affect total revenue.
Highlights
Accepted: February 9, 2017Published: March 17, 2017
This paper presents a mathematical model for a three-level supply chain, including a producer, a distributor, and a retailer
The production cost eventually has a declining trend that can be demonstrated in terms of cubic function and the resulted optimal pricing model can be modeled in Geometric Programming (GP)
Summary
OPEN ACCESS Citation: Moosavi Tabatabaei SR, Sadjadi SJ, Makui A (2017) Optimal pricing and marketing planning for deteriorating items. Optimal pricing and marketing planning plays an essential role in production decisions on deteriorating items. The proposed study considers the production of a deteriorating item where demand is influenced by price, marketing expenditure, quality of product and after-sales service expenditures. The proposed model is formulated as a geometric programming with 5 degrees of difficulty and the problem is solved using the recent advances in optimization techniques. The preliminary results indicate that with the change in parameters influencing on demand, inventory holding, inventory deteriorating and set-up costs change and significantly affect total revenue
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