In the era of borderless international marketing and e-commerce, selecting the appropriate partners is a precondition for success.  This paper focuses on facilitating the partner selection process through the application of Particle Swarm Optimization (PSO) Algorithm. It also aims to resolve the problems of defective supply-chain, considering the uncertainties involved in real life. The uncertainties may occur in the production system as well as in transportation time, machine hour, the distance between the partners of different echelon etc. At first, we study these stochastic data and determine their parameters. Once the characteristics are determined, they are converted in a generalized form to be included into a model formulated for solving the defective supply chain. In the era of borderless international marketing and e-commerce, selecting the appropriate partners is a precondition for success.  This paper focuses on facilitating the partner selection process through the application of Particle Swarm Optimization (PSO) Algorithm. It also aims to resolve the problems of defective supply-chain, considering the uncertainties involved in real life. The uncertainties may occur in the production system as well as in transportation time, machine hour, the distance between the partners of different echelon etc. At first, we study these stochastic data and determine their parameters. Once the characteristics are determined, they are converted in a generalized form to be included into a model formulated for solving the defective supply chain.