This study proposes a mixed-integer multi-objective integrated mathematical model solving facility location and order allocation optimization problems simultaneously in a two-echelon supply chain network.The proposed problem is motivated by a factoyless concept and, by providing a dynamic decision-making solution under a multi-period time horizon. Within the model, we also determine the optimal replenishment amounts of production facilities by the multi-objective functions. The multi-objective functions include minimization of the total cost, rejected and late delivery units and, maximization of the assessment score of the selected suppliers. The studied dynamic decision model is significant for the cost-efficient management of companies' supply chain networks. The mixed-integer mathematical model is developed by the LP-metric method and it is solved by the GAMS optimization software. Due to the NP-hard structure of the problem, for large-scale instances, we utilize the Multi-Objective Particle Swarm Optimization (MOPSO) and Multi-Objective Vibration Damping Optimization (MOVDO) heuristic solution approaches.Numerical results show that for large-scale problems, the MOPSO method performs better in Pareto solutions and decrease run times. However, the MOVDO method performs better regarding the Mean Ideal Distance and the Number of Solutions Cover surface criterion. The developed solution approach by this paper is a generic model which can be applied for any two-level network for simultaneous optimization of supplier selection, location determination of facilities and their replenishment amounts.