OPTIMASI ORDER SCHEDULLING DENGAN INTEGRASI MODEL EVALUASI SUPPLY CHAIN

Abstract

Abstract Industrial processing of chicken/native is one of the many industry-based food productions. These industry players realize that to provide cheap products, quality, and fast is not enough to make improvements in the company's internal only. But also takes the role of all parties, from suppliers who provide raw materials, transportation companies that send raw materials from suppliers to the industry, as well as the distribution network delivering products into the hands of customers. Performance improvement requires the presence of Supply Chain performance measures beforehand. The results of these measurements will be used as reference for improvement of performance of the Supply Chain. The reason the use of AHP and MILP itself because of these two methods are expected to provide the best solution of existing problems, which AHP method can determine the weighting or desired supplier selection criteria from existing suppliers. While the MILP method alone is expected to maximize profits by considering the risks. The results of the application of the AHP method known value of most major sub-criteria weights that supplier B with value at a price of 0.594 sub-criteria, sub-criteria weights alternative on the quality of 0.493, the sub-criteria weights alternative delivery time of 0.387, an alternative to the sub-criteria weights accuracy number of 0493, and the weight alternative to the sub-supplier performance criteria for 0.374. While based on the application of linear programming methods of forecasting results are known supplier B has a stock of goods which are more stable than other suppliers to stock inventory in July amounted to 18.116 tails, august amounted to 18.524 tails, September amounted to 19.033 tails, October amounted to 19.542 tails, in month of november to 20.068 tails, december amounted to 20.559 tails, and in January next at 21.068 tails.

Keywords

• Analytic Hierarchy Process
• Mixed Integer Linear Programming
• Supply Chain Management