This paper proposes an adaptive fuzzy control application to support a vendor managed inventory (VMI). The methodology applies fuzzy control to generate an adaptive smoothing constant in the forecast method, production and delivery plan to eliminate, for example, the rationing and gaming or the Houlihan effect and the order batching effect or the Burbidge effects and finally the Bullwhip effect...

This paper recommends a scaling factors fine-tuning fuzzy logic control approach to optimize the dynamic performance of one typical vendor managed inventory supply chain with automatic pipeline, inventory and order based production control system(VMI-APIOBPCS), based on complex fuzzy control theory. The first thing is to embed a dual-input single-output fuzzy logic controller into the system ba...

The major purpose of this paper is to apply a stochastic single-period inventory management approach to analyze optimal cash management policies with fuzzy cash demand based on fuzzy integral method so that total cost is minimized. We will find that, after defuzzification, the cash-raising amounts and the total costs between the fuzzy case and the crisp case are slightly different when the vari...

Inventory decisional environment of short life-cycle products is full of uncertainties arising from randomness and fuzziness of input parameters like customer demand requiring modeling under hybrid uncertainty. Prior inventory models incorporating fuzzy demand have unfortunately ignored stochastic variation of demand. This paper determines an unambiguous optimal order quantity from a set of n f...

Cost and operation of inventory depends a great deal on what happens to demand when the system is out of stock. In real inventory systems, it is more reasonable to assume that part of the excess demand is backordered and the rest is lost. However, the amount of backorders (or lost sales) often incurs disturbance due to various uncertainties. To incorporate this reality, this article attempts to...

In this research we concentrate on developing a bifuzzy model for a Single-period inventory problem. The conventional studies have focused on the cases that the demands are probabilistic and follow certain distribution function; or the demands are considered as fuzzy variables; or the demands is expressed by random fuzzy variable. Recently, fuzzy random variables have been applied to some decis...

A novel paradigm for adaptation in discrete event dynamic systems control is presented. The general idea is then applied, through simulations, to an inventory system. A fuzzy adaptation module is built from few optimal examples generated using a genetic algorithm. The fuzzy module is then capable of adapting the inventory policy achieving much better results than a static policy.

Multi-objective inventory models of deteriorating items have been developed with vague and imprecise information about available storage area. Here, the objectives are (i) to maximize the profit, (ii) to minimize the wastage cost due to deterioration and (iii) to minimize the total production cost. These objectives are also fuzzy in nature. In these models, production rate is a decision variabl...

In this paper, an integrated inventory model is developed from the perspective of a single vendor and multi-buyers for deteriorating items under fuzzy environment and inflation. In the development of the model, it is assumed that all costs parameters, demand and the production rates are imprecise in nature; they are represented by the trapezoidal fuzzy numbers, as these parameters are not const...

A fuzzy random model of Combined Location Routing and Inventory Problem (CLRIP) has been presented with continuous review inventory policy in B2C distribution environment for the first time. Demands of customers and distribution centers are uncertain and have been assumed to be fuzzy random variables. To solve the model, first the expected value of fuzzy random variable and the possibilistic me...