Three-level supply chain modeling with incomplete and uncertain information in order to analyze its effects

The present study presents a three-tier model with incomplete and uncertain information of supply chain needs, benefits and services. Objectives of the issue include determining the best decision to determine the optimal order amount and shortage for the manufacturer and the selling price of each player according to the shortage, discount and maintenance costs, purchase and marketing to achieve maximum revenue, minimum costs and The sum is the maximum possible profit for all the players participating in the chain. To solve the model, Gamz software and meta-heuristic algorithms have been used and finally, Given the complexity of the complexity of closed-loop supply chain problems, the problem ahead cannot be solved in a reasonable time for real-world dimensions. Therefore, to solve it, the meta-heuristic approach in the form of genetic algorithms and optimization of particle aggregation and the combination of these two algorithms have been used. The results show that the combined algorithm of genetics and particle swarming has a better situation compared to genetic and particle swarming algorithms.