Phan Nguyen Ky Phuc

Analyzing the ranking method for L-R fuzzy numbers based on deviation degree

Ranking fuzzy numbers based on their left and right deviation degree (L-R deviation degree) has attracted the attention of many scholars recently, yet most of their ranking methods have two systematic shortcomings that are usually ignored. This paper addresses these shortcomings and proves them through mathematical proofs instead of providing counter-examples. Applying our analyses will help other authors avoid some common errors when building their own ranking index functions. We use Asadys ranking index function (2010) as an example when we present our arguments and proofs and provide fully detailed analyses of two of the ranking index functions herein. Based on these analyses, an algorithm for detecting inconsistencies in ranking results is proposed, and numerical examples are given to illustrate our arguments.

Effects of dominance on operation policies in a two-stage supply chain in which market demands follow the Bass diffusion model

The Bass model offers several successful applications in forecasting the diffusion process of new products. Due to its potential and flexibilities, the application of this model is not only limited now to forecasting, but also extends to other fields such as analyzing a supply chain’s responses, optimizing production plans, and so forth. This study investigates inventory and production policies in a two-stage supply chain with one manufacturer and one retailer, in which the market demand process follows the Bass diffusion model. The model assumes the market parameters and essential information are available and ready for access. This study then applies dynamic programming and heuristic algorithm to find the optimal policies for each stage under different scenarios.