|
Optimization inventory-related decisions under an outsourcing supply chain management using response surface methodology
|
| |
|
|
|
چکیده: (8 مشاهده) |
The current research provides a mixed integer nonlinear mathematical programming model for a company that operates with several stores and multiple products, in which demand for each customer is characterized using fuzzy logic by triangular numbers, while the replenishment policy of each store for any product is the popular economic order quantity (EOQ) model under backorder. The throughput, dispatch, and budget constraints are considered in the proposed EOQ model. The objective is to integrate a vendor selection problem and EOQ policy, in which a multi-sourcing strategy is considered. In the proposed strategy, the ordered value of each store for any product can be split between one or more vendors. As such, a set of selected vendors can replenish each store for each product. This research aims to answer the following question as follows: (i) which vendors are chosen; (ii) which store is allocated to the selected vendors for each product; (iii) what is the optimal value for the inventory decisions.
The aim is to reduce the total cost of the company, including costs related to the vendor selection decisions along with the inventory decisions. To solve the mathematical model, a novel and practical genetic algorithm (GA) is developed then the response surface methodology (RSM) is utilized to tune its parameters. At the end, some numerical instances under different categories are evaluated to explain the applicability of the proposed approach.
|
|
| |
|
|
متن کامل [PDF 722 kb]
(5 دریافت)
|
نوع مطالعه: كاربردي |
موضوع مقاله:
Supply chain optimization policy for a supplier selection problem: a mathematical programming approach
دریافت: 1404/5/14 | پذیرش: 1404/10/3 | انتشار: 1404/10/10
|
|
|
|
|
|
|
| ارسال نظر درباره این مقاله |
|
|
|
