Hui Ming Wee

A simple and better algorithm to solve the vendor managed inventory control system of multi-product multi-constraint economic order quantity model

This research presents an alternative heuristic algorithm to solve the vendor management inventory system with multi-product and multi-constraint based on EOQ with backorders considering two classical backorders costs: linear and fixed. For this type of inventory system, the optimization problem is a nonlinear integer programming (NLIP). Several numerical examples are given to demonstrate that the proposed heuristic algorithm is better than the previous genetic algorithm published based on three aspects: the total cost, the number of evaluations of the total cost function and computational time. Furthermore, the proposed algorithm is simpler and can be implemented by any people.

Economic order quantity model for deteriorating items with planned backorder level

In this study, a deteriorating inventory problem with and without backorders is developed. From the literature search, this study is one of the first attempts by researchers to solve a deteriorating inventory problem with a simplified approach. The optimal solutions are compared with the classical methods for solving deteriorating inventory model. The total cost of the simplified model is almost identical to the original model.

Economic production quantity model for deteriorating inventory with random machine unavailability and shortage

Both random machine unavailability and shortage are common occurrences in manufacturing industries. In this paper, machine unavailability is considered in deriving an economic production quantity (EPQ) model for deteriorating items. We develop four EPQ models for deteriorating inventory with random machine unavailability and shortage. The study considers lost sales, backorder and two kinds of machine unavailability distributions. Numerical examples are provided to illustrate the theory. Key parameter changes that affect costs are shown in the sensitivity analysis. From the results of the sensitivity analysis, it is shown that the random machine unavailability parameter and holding cost have significant effects on the optimal total cost and production down-time.

Economic production quantity models for deteriorating items with rework and stochastic preventive maintenance time

Economic production quantity (EPQ) models for deteriorating inventory have been investigated by many researchers in recent years. In this paper, we develop EPQ models for deteriorating items with rework and stochastic preventive maintenance time. The models are solved using a search method, since a closed form solution cannot be derived. A numerical example and sensitivity analysis are provided to evaluate the models. The sensitivity analysis shows that the deteriorating cost has a significant effect on the optimal inventory cost; however, the production and the demand rate have the most significant effect on the optimal total cost and the optimal production up-time period.

An economic production quantity model for deteriorating items with preventive maintenance policy and random machine breakdown

In recent years, many researches on economic production quantity (EPQ) models with machine breakdown and preventive maintenance have been developed, but few of them have developed integrated models for deteriorating items. In this study, we develop EPQ models for deteriorating items with preventive maintenance, random machine breakdown and immediate corrective action. Corrective and preventive maintenance times are assumed to be stochastic and the unfulfilled demands are lost sales. Two EPQ models of uniform distribution and exponential distribution of corrective and maintenance times are developed. An example and sensitivity analysis is given to illustrate the models. For the exponential distribution model, it is shown that the corrective time parameter is one of the most sensitive parameters to the optimal total cost.

Revisiting lot sizing for an inventory system with product recovery

This note investigates the study by Teunter (2004) [1] on lot sizing for inventory systems with product recovery where lot sizing formulae for two recovery policies ((1,R) and (P,1)) are derived. Instead of applying the classical optimization technique, we develop an integrated solution procedure for each of the two policies using algebraic approaches. Numerical analysis show that our examples result in a lower total cost for both policies.

Optimal economic order quantity for buyer–distributor–vendor supply chain with backlogging derived without derivatives

In this article, we first complement an inappropriate mathematical error on the total cost in the previously published paper by Chung and Wee [2007, ‘Optimal the Economic Lot Size of a Three-stage Supply Chain With Backlogging Derived Without Derivatives’, European Journal of Operational Research, 183, 933–943] related to buyer–distributor–vendor three-stage supply chain with backlogging derived without derivatives. Then, an arithmetic–geometric inequality method is proposed not only to simplify the algebraic method of completing prefect squares, but also to complement their shortcomings. In addition, we provide a closed-form solution to integral number of deliveries for the distributor and the vendor without using complex derivatives. Furthermore, our method can solve many cases in which their method cannot, because they did not consider that a squared root of a negative number does not exist. Finally, we use some numerical examples to show that our proposed optimal solution is cheaper to operate than theirs.

Optimal unit price and credit period for price sensitive demand and random supply

In this study, the authors develop a supplier-retailer optimal integrated strategy where the retailers demand is price sensitive and the suppliers supply is random. It is assumed that the suppliers supply follows a normal distribution and the supplier may offer credit period to the retailer. The expected profit is maximised with respect to the unit price charged and the credit period offered by the supplier. The computational steps are provided to obtain the suppliers and the retailers decision variables under individual (non-cooperative) as well as joint (cooperative) strategies. The sensitivity analysis of the parameters is carried out using a numerical example. The authors observe that it is beneficial to consider negotiating the optimal pricing and trade credit policies.

Stackelberg game for two-level supply chain with price markdown option

Vendor–retailer collaboration has an important role in supply chain management. Although vendor–retailer collaboration results in better supply chain profit, collaboration is difficult to realize. This is because most vendors and retailers try to optimize their own profit. This paper applies the Stackelberg game with stochastic demand for the vendor–retailer system. The vendor as a leader determines the product price, and the retailer decides order quantity and frequency of price markdown. This study develops example and sensitivity analyses to illustrate the theory. Results show that the price markdown option has a better total supply chain profit than without a price markdown policy, and the vendor receives more benefit. For different demand variances, the retailer profit is more sensitive than the vendor profit.

Optimal coordinated supply chain strategy with price and time sensitive demand

In this study, inventory models are developed for coordinated supply chain using Stackelberg game framework. In the proposed model, customer demand is assumed to be price and time sensitive. The buyer attempts to adjust retail selling prices by charging premium or offering discount to the floor selling price depending upon the optimistic or declining market conditions. The aim of this research paper is to analyse the optimal pricing policy that maximises total profit for both the players under the principles of coordination, and competition. Some numerical examples are given to study the model. The results show that the vendor gets more advantage when the collaborative model is applied and the buyers profit is bigger in the Stackelberg game model than the collaborative model.