Inventory policies in a fuzzy uncertain supply chain environment

Expert Systems with Applications, 2009

Applied Mathematical Modelling, 2008

An inventory model of deteriorating seasonal products with Maximum Retail Price (MRP) for a wholesaler having showrooms at different places under a single management system is considered under random business periods with fuzzy resource constraints. The wholesaler replenishes the products instantaneously and earns commissions on MRP which vary with the ordered quantities following All Unit Discount (AUD), Incremental Quantity Discount (IQD) or IQD in AUD policy. Demand at showrooms are imprecise and related to selling prices by 'verbal words' following fuzzy logic. The wholesaler shares a part of commission with customers. The business periods follows normal distribution and converted to deterministic ones through chance constraint technique. The fuzzy space and budget constraints and fuzzy relations are defuzzified using possibility measures, surprise function and Mumdani fuzzy inference technique. The model is formulated as profit maximization for the wholesaler and solved using a real coded Genetic Algorithm (GA) and illustrated through some numerical examples and some sensitivity analysis. A real-life problem of a developing country is presented, solved using the above mentioned procedures and an appropriate inventory policy is suggested.

International Journal of Production Economics, 1999

This paper considers a production supply chain (SC) with all facilities in a serial connection. The SC includes inventories and production facilities between them. It is assumed that the SC operates in an uncertain environment. Uncertainty is associated with: (1) customer demand, (2) supply deliveries along the SC and (3) external or market supply. Uncertainties are described by vague and imprecise phrases that are interpreted and represented by fuzzy sets. The SC fuzzy model described in this paper is developed to determine the order quantities for each inventory in the SC in the presence of uncertainties, that give an acceptable service level of the SC at reasonable total cost. Two control concepts of the SC are treated: (1) decentralised control of each inventory and (2) partial coordination in the inventories control. A special purpose simulator has been developed for examining the dynamics and performance of all the parts of the SC and the SC as a whole. Various simulation tests have been carried out to assess particularly the effects of uncertain external supply on the SC service level. Different approaches to improve SC performance in an uncertain environment have been simulated and analysed.

IAEME, 2019

In this paper, we have analyzed a serial operational level Supply Chain Performance like fill rate, Build –To - Stock etc., under an uncertainty environment for the optimality using a stochastic customer order. It evaluates minimum cost in supply chain, simultaneously optimize quantitative decision variables and illustrates the significance of capacity variable. Numerical examples are presented to illustrate the benefit of the proposed strategies and the effects of changes on the cost and parameters are studied

International Journal of Approximate Reasoning, 2010

The paper considers an inventory model with backorders in a fuzzy situation by employing two types of fuzzy numbers, which are trapezoidal and triangular. A full-fuzzy model is developed where the input parameters and the decision variables are fuzzified. The optimal policy for the developed model is determined using the Kuhn-Tucker conditions after the defuzzification of the cost function with the graded mean integration (GMI) method. Numerical examples and a sensitivity analysis study are provided to highlight the differences between crisp and the fuzzy cases.

Computer Integrated Manufacturing Systems, 1994

Invenory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

International Journal for Research in Applied Sciences and Biotechnology, 2021

In this paper we have developed a supply chain production inventory model for deteriorating items with shortage under Fuzzy environment. The formulae for the optimal average system cost, stock level, backlog level and production cycle time are derived when the deterioration rate is very small. In reality it is seen that we cannot define all parameters precisely due to imprecision or uncertainty in the environment. So, we have defined the inventory parameter deterioration rate as triangular fuzzy numbers. The signed distance method and graded mean integration method have been used for defuzzification. Numerical examples are taken to illustrate the procedure of finding the optimal total inventory cost, stock level and backlog level. Sensitivity analysis is carried out to demonstrate the effects of changing parameter values on the optimal solution of the system.

2012

Fu zzy set theory is primarily concerned with how to quantitatively deal with imp rec ision and uncertainty, and offers the decision maker another tool in addition to the classical deterministic and probabilistic mathematical tools that a re used in modeling real-world problems. The present study investigates a fuzzy economic order quantity model for deteriorating items in which demand increases with time. Shortages are allowed and fully backlogged. The demand, holding cost, unit cost, shortage cost and deterioration rate are taken as a triangular fuzzy nu mbers. Graded Mean Representation, Signed Distance and Centroid methods are used to defuzzify the total cost function and the results obtained by these methods are compared with the help of a numerical example. Sensitivity analysis is also carried out to explore the effect of changes in the values of some of the system parameters. The proposed methodology is applicable to other inventory models under uncertainty.

The Annals of the University of Oradea. Economic Sciences

In inventory and production decision problems, decision makers are interested to identify the optimal inventory and production level. In a certain decision environment, the optimal inventory level could be determined through traditional inventory methods and the optimal ptoduction level could be determined through linear programming algorithms. In an uncertain decision environment, the traditional methods and algorithms can not provide efficient and relevant solutions for these levels, due to the vague and changing parameters. In this case it is neccesary to develop new methods and models that can deal with vague variables and provide optimal levels. In this paper, the optimal inventory and production levels are determined through a single model that uses fuzzy linear programming. This new model is Fuzzy Optimistic-Reasonable-Pessimistic Inventory Model. It has three scenario: optimistic, reasonable and pessimistic, that are defined through triangular fuzzy numbers. In this way, dec...

International Journal on Design and Manufacturing Technologies, 2015

A real Supply Chain (SC) functions in an uncertain environment. Different type of uncertainties exist along the SC. These are random. Uncertainty appears in customer demand, production and supply. The SC models developed till now either neglect uncertainty or considered it approximately by the use of probability concepts. This paper concentrates on developing a fuzzy model for analyzing supply chain dynamics and measures of performance during a finite time horizon. It has been seen that uncertain customer demand and uncertain supply along the supply chain have great impact on supply chain behavior. In this paper satisfaction of customer is examined in an uncertain environment using fuzzy concept. This model gives very useful results to understand the real situation of the demand and production. These models help to reduce lead time, holding cost and maximize the profit as well. The proposed scheme provides managerial insights on the impact of the decision making in all the supply chain elements including suppliers, manufacturers, warehouses, transporters, retailers, and customers.