Fuzzy mixture inventory model with variable lead-time based on probabilistic fuzzy set and triangular fuzzy number

Authors:
Hung-Chi Chang;Jing-Shing Yao;Liang-Yuh Ouyang
Affiliations:
Department of Logistics Engineering and Management National Taichung Institute of Technology Taichung 404, Taiwan, R.O.C.;Department of Mathematics, National Taiwan University Taipei 251, Taiwan, R.O.C.;Department of Management Sciences, Tamkang University Taipei 106, Taiwan, R.O.C.
Venue:
Mathematical and Computer Modelling: An International Journal
Year:
2004

Citing 6
Cited 1

Fuzzy set theory—and its applications (3rd ed.)

Fuzzy set theory—and its applications (3rd ed.)
Backorder fuzzy inventory model under function principle

Information Sciences: an International Journal
Fuzzy economic production for production inventory

Fuzzy Sets and Systems
Fuzzy inventory without backorder for fuzzy order quantity and fuzzy total demand quantity

Computers and Operations Research
Ranking fuzzy numbers based on decomposition principle and signed distance

Fuzzy Sets and Systems - Special issue on fuzzy numbers and uncertainty
A minimax distribution free procedure for mixed inventory model involving variable lead time with fuzzy demand

Computers and Operations Research

A hybrid method of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with stochastic replenishments and fuzzy demand

Information Sciences: an International Journal

Quantified Score

Hi-index	0.98

Visualization

Abstract

This article considers the fuzzy problems for the mixture inventory model involving variable lead-time with backorders and lost sales. `Ve first use the probabilistic fuzzy set to construct a new random variable for lead-time demand, and derive the total expected annual cost in the fuzzy sense. Then, the average demand per year is fuzzified as the triangular fuzzy number. For this case, two methods of defuzzification, namely signed distance and centroid, are employed to find the value of total expected annual cost in the fuzzy sense. Next, the backorder rate of the demand during the stock-out period is also fuzzified as the triangular fuzzy number, and the value of total expected annual cost in the fuzzy sense is derived using the signed distance. For the proposed models, we provide a solution procedure to find the optimal lead-time and the optimal order quantity such that the total expected annual cost in the fuzzy sense has a minimum value.