Single-period problem which is called newsboy problem, is one of the commonplace problem in inventory control. Using inventory control models in each stage of industry cycle has become commonly to determine order quantities and commodity inventory. In this paper, optimizing a bi-objective, multi-product, multi-constraint, single-period problem is considered with incremental discount policy in purchasing commodity to find the order quantities which will be maximized both expected profit and minimized service level. Constraints are budget and warehouse capacity. In addition, decision variables are real and it is assumed that holding and shortage costs occur at the end of a period. Formulation of the problem is presented and shown to be a mixed integer nonlinear programming model. Furthermore, Multi- Objective Decision Making (MODM) approaches are utilized to solve the model with meta-heuristic algorithms. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are provided to find an approximate optimum solutions of the problem. After applying RSM method to calibrate the parameters of both algorithms, their performances in solving instances compare in terms of solution quality of both algorithms. In final, GAMS program is applied for validating the solutions.