Fuzzy approximate reasoning toward Multi-Objective optimization policy: Deployment for supply chain programming

To make a policy and decision for an appropriate set of optimizer algorithms is an important and controversial issue. It is significant especially when we want to consider more than a single objective and have to use multi-objective applications. The aim of this paper is to consider procedural fuzzy approximate reasoning to infer which one of the Multi-Objective Evolutionary Algorithms (MOEAs) could play a role in the suitable set as prevalent tool. The proposed procedure is put into practice for an invented bi-objective programming in the supply chain and three numbers of similar applications from the same family, i.e. NSGA-II, NRGA, and PESA-II are deployed.