Affiliations: [a]
Business School, University of Shanghai for Science and Technology, Shanghai, China
| [b]
The Logistics Institute-Asia Pacific and NUS Business School, National University of Singapore, Singapore
Correspondence:
[*]
Corresponding author. Shaojian Qu, Business School, University of Shanghai for Science and Technology, Shanghai 200093, China. E-mail: [email protected].
Abstract: This paper applies the credibility distribution of fuzzy variables in uncertainty theory to formulate a fuzzy optimization model, so as to study the coordination mechanism of a distribution supply chain system with fuzzy demand. This practical system, focusing on the demand side of the supply chain, comprises multi-period, multi-manufacturer, multi-retailer, and multi-consumer. Next, using a novel modified sequence quadratic programming algorithm, the optimal order quantity, sales volume of the retailers, and the maximum expected return of the distribution supply chain are obtained. The effects of the wholesale price, retail price, and inventory cost on the expected return are also analyzed. Finally, the usfulness of the proposed modified sequence quadratic programming algorithm is compared against the conventional MATLAB optimal toolbox and genetic algorithm. Our computational results validate in favour of the proposed algorithm in terms of the computational time, number of iterations, and convergence rate.
Keywords: Distribution supply chain, fuzzy demand, uncertainty theory, algorithm
