The results of the numerical experiments section should be better analyzed and further developed, page 4. Develop the conclusions section to include the unique contributions of the paper and innovation of the research, page 8. Joint Decision on Integrated Supplier Selection and Inventory Control of Inventory System Consideration Purchase Discount.
Methodology
Number: 2 Author: Subject: Comment on Text Date Elaboration of the mathematical model for each uncertain parameter. Number: 1 Author: Subject: Comment on text Date Ensure a good format, equation no. must be within the margin.
Numerical Experiment
Number: 1 Author: Subject: Text Comment Date Discuss and interpret the results of figures 3-6.
Concluding Remarks and Future
Develop the conclusions section to include the paper's unique contributions and research innovation. Number: 3 Author: Subject: Comment on text Date Explain future research related to this topic. Our title document is Joint Decision on Integrated Vendor Selection and Inventory Management of the Inventory System Considering Purchasing Discount.
Summary—Inventory control and supplier selection are two important parts of supply chain and management. In addition, if some suppliers give a purchase discount for their product, it is interesting how to determine the optimal strategy. In this paper, the authors propose a mathematical model in mixed quadratic integer programming with a partial objective function that can be used to determine the optimal strategy for the integrated supplier selection problem and the inventory control problem of a multi-product inventory system by considering the purchase discount.
Stock control refers to bringing the stock level of each product to a reference level given by the decision maker. The authors formulate two mathematical models which are a model in the deterministic environment where all parameters are known and a model in the probabilistic environment where the demand is random.
Introduction
Let t denote the stage of the problem, xt denote the decision variable at stage t and t denote the event space at stage t. A scenario is one possible outcome in the future based on the realization of the random parameters and scenario tree is the summary of all possible combinations of outcomes illustrated by Fig. The decision is made based on the previous decisions and the realization of the random parameters.
Symbols of the parameters and variables of the problem are used for mathematical model formulation. Let the number of the supplier be S and the number of the period the problem will be solved is T. Let Pi denote the probability of scenario i and denote the event space of the problem for any period.
The evolution of the inventory level of all products and their reference levels can be seen in Figure 4. Let the demand value for p2 be 200 units for each time period and the demand value for p3 be 300 units for each time period. Based on the scenarios given in Table 3, the optimal decision of a time period can be determined after the random parameter of the corresponding time period is revealed.
The optimal decision for time periods 2 and 3 can be determined after the demand of p1 in time periods 2 and 3 is revealed. It can be observed that for period 1 and 2 the actual inventory level of each product is closed to the reference level. For time period 3, the actual inventory level follows the reference level, although there is a sufficiently large gap between them.
To observe how the comparison between the inventory level of each product and its reference level, the authors evaluate the model in 10 time periods and the result, i.e. the authors observe that this was caused by the number of time period evaluations, which is 3 time periods for each model evaluation, meaning that it makes an assumption to the model that the problem is optimized for only 3 time periods and there is no optimization thereafter. The last numerical experiment is used to analyze the impact of the demand uncertainty on the expected total cost.
Concluding Remarks and Future Research
From Figure 7, it can be seen that the total expected cost becomes larger if the standard deviation of demands becomes larger.
Acknowledgment
Banwet, "Expert Systems with Applications A Nonlinear Mixed Integer Program for Modeling Dynamic Supplier Selection Problem. Kara, "Expert Systems with Applications Selection with an Integrated Method in Unknown Environment," Expert Syst. Üstün, "An Integrated Multiobjective Decision Process for Supplier Selection and order allocation,” Omega , vol.
Tabrizi, "An Integrated Framework for Knowledge-Based Network Supplier Selection and Configuration Using QFD, ANP, and Mixed Integer Programming Model", vol. Izadikhah, "Group Decision Making Process for Supplier Selection by TOPSIS Method under Intuitionistic Interval Fuzzy Numbers," vol. Munawwaroh, "Hybrid Mathematical Model of Piecewise Holding Cost Inventory System and Its Optimal Strategy," in.
Wen, "A Hybrid Multiple Criteria Group Decision-Making for Green Supplier Selection in the TFT-LCD Industry," vol. Wicaksono, “Optimal strategy for multi-product inventory system with supplier selection using predictive control model”, Procedia Manuf. Tabrizi, "An Integrated Framework for Supplier Selection and Configuration-Based Networks Using QFD, ANP, and the Mixed-Integer Programming Model", vol.
Munawwaroh, "Hybrid mathematical model of inventory system with piecewise l strategy," in 2015 International Conference on Advanced Mechatronics, Intelligent Manufacturing and Industrial Automation (ICAMIMIA), 2015, Y. Tosun, "An Integrated Methodology for Supplier Selection under the Presence of Vagueness: A Case in Banking Sector, Turkey,” vol.Wen, “A Hybrid Multiple Criteria Group Making Approach for Green Supplier Selection in LCD Industry,” vol.
Yu, “Selecting Ideal Coal Suppliers for Thermal Power Plants Using a Matter-Element Expansion Model with an Integrated Empowerment Method for Sustainability,” Vol. Economic Analysis of Biomass Supply Chains: A Case Study of Four Competing Bioenergy Plants in Northwestern Ontario,” Vol. Mahmoodi, “A New Hybrid Fuzzy TOPSIS-TODIM Method for Green Supplier Selection Using Fuzzy Time Function,” Vol.
