It’s an assignment in inventory ABC classification and supply chain management.
The difficulty is using and implementing a Differential Evolution algorithm to generate/optimize Criteria Weight (values) using “Excel Optimization” of the attached research paper entitled as (A new hybrid multi-criteria ABC inventory classification model based on Differential Evolution and Topsis).
I kindly request you to help by providing me with a clear illustrative implementation (step by step excel optimization solution and notes). Use Excel Optimization to generate criteria weights (values) of the two data-sets, and based on the three criteria namely as Average Unit Cost (AUC), Annual Dollar Usage (ADU) and Lead Time in day (LT).
Note: Three full texts of research papers are attached…
Main source: A new hybrid multi-criteria ABC inventory classification model based on Differential Evolution and Topsis
1st supported source: On rank reversal and TOPSIS method
2nd supported source: A comparative study of MCIC.
Send me back the attached excel file including the detailed steps/ necessary notes of using DE to infer criteria weight for the case of:
Sheet 1 and 2 of Excel file including two data-sets of 47 and 1500 inventory items is attached using (equal weight technique) since the obstacle is how to used DE to optimize CWs so we can then apply them to TOPSIS…
finally my question is:
Based on for the two data-sets, would values of the generated criteria weights via DE be changeable depending on the size of decision matrix (e.g:47 items vs 2000 items or 200,000 items)?