meta-heuristic algorithms in solving the perishable supply chain network problem considering the queuing system based on robust possibilistic programming

In a real world, there are some products and goods such as meat, vegetables, fruits and flowers that decay during the time. the producer has to produce more than the market demand due to the decay of some of the perishable goods. the perishable goods affect the production planning, goods preservation policy and the retailer’s decision making. the retailer should also consider the good’s perishability in her/his decision making. therefore, one of the attractive and considerable subcategories of the supply chain management is the appropriate design of the chain network in supplying the perishable goods in which the main challenge is decreasing the expenses of production and preservation and also the perishable goods is one of the challenges of the perishable goods. in this article, a model of supply chain for perishable goods has been considered which is used to control the uncertain parameters by robust possibilistic programming and the meta-heuristic algorithms such as pso, alo and gwo are used to solve it. the results show that the gwo algorithm is much more efficient than other algorithms. to compare these algorithms, the means of total cost and cpu-time have been used. also, t-test was used to study the significant index means derived from the meta-heuristic algorithms which shows no significant difference between the objective function and the cpu-time.