Deterministic lot-size inventory models with shortages and deterioration for fluctuating demand

Authors:
Jinn-Tsair Teng;Maw-Sheng Chern;Hui-Ling Yang;Yuchung J. Wang
Affiliations:
Department of Marketing and Management Sciences, The William Paterson University of New Jersey, Wayne, NJ 07470, USA;Department of Industrial Engineering, National Tsing Hua University, Hsinchu 30043, Taiwan, ROC;Center of General Education, Hung Kuang Institute of Technology, Taichung 433, Taiwan, ROC;Department of Mathematical Sciences, Rutgers University, Camden, NJ 08102, USA
Venue:
Operations Research Letters
Year:
1999

Citing 2
Cited 7

A sensitivity analysis of a (ti , Si) inventory policy with increasing demand

Operations Research Letters
A deterministic inventory replenishment model with a linear trend in demand

Operations Research Letters

On an inventory model for deteriorating items with stock dependent and time-varying demand rates

Computers and Operations Research
Optimal Ordering Policy for Deteriorating Items with Partial Backlogging under Permissible Delay in Payments

Journal of Global Optimization
A backward recursive algorithm for inventory lot-size models with power-form demand and shortages

International Journal of Systems Science
Optimal integrated policies for a single-vendor single-buyer time-varying demand model

Computers & Mathematics with Applications
An optimal replenishment policy for deteriorating items with time-varying demand and partial backlogging

Operations Research Letters
An optimal replenishment policy for deteriorating items with time-varying demand and partial-exponential type - backlogging

Operations Research Letters
Manufacturing production plan optimization in three-stage supply chains under Bass model market effects

Computers and Industrial Engineering

Quantified Score

Hi-index	0.00

Visualization

Abstract

We establish various inventory replenishment policies. We then analytically identify the best alternative among them based on the minimum total relevant costs. Finally, we prove that the relevant cost is convex with the number of replenishments. Consequently, the search for the optimal replenishment number is reduced to finding a local minimum.