Ilkyeong Moon

A note on lead time and distributional assumptions in continuous review inventory models

Abstract Scope and Purpose There is a rapidly growing literature on modelling the effects of investment strategies to control givens such as setup time, setup cost, quality level and lead time. Recently, a continuous review inventory model with a mixture of backorders and lost sales in which both lead time and the order quantity are decision variables has been studied. The objectives of this paper are twofold. Firstly, we want to correct and improve the recently studied model by simultaneously optimizing both the order quantity and the reorder point. A significant amount of savings over the model can be achieved. We illustrate these savings by solving the same examples in the study. Secondly, we then develop a minimax distribution free procedure for the problem. Recently, there have been some studies on lead time reduction to provide more meaningful mathematical models to decision makers. Ouyang et al. study a continuous review inventory model in which lead time is a decision variable. However, their algorithm cannot find the optimal solution due to the flaws in the modeling and the solution procedure. We present a complete procedure to find the optimal solution for the model. In addition to the above contribution, we also apply the minimax distribution free approach to the model to devise a practical procedure which can be used without specific information on demand distribution.

An EPQ model with inflation in an imperfect production system

In this paper, a production inventory model is considered for stochastic demand with the effect of inflation. Generally, every manufacturing system wants to produce perfect quality items. However, due to real-life problems (labor problems, machine breakdown, etc.), a certain percentage of products are of imperfect quality. The imperfect items are reworked at a cost. The lifetime of a defective item follows a Weibull distribution. Due to the production of imperfect quality items, a product shortage occurs. The profit function is derived by using both a general distribution of demand and the uniform rectangular distribution of demand. Computational experiments along with graphical illustrations are presented to discuss the optimality of the probability functions.

Economic order quantity models for ameliorating/deteriorating items under inflation and time discounting

The items that incur a gradual loss in quality or quantity over time while in inventory are usually called deteriorating items. In reality, there are some items whose value or utility or quantity increase with time and those items can be termed as ameliorating items. In this paper, an effort has been made to incorporate these two opposite physical characteristics of stored items into inventory model. We develop models for ameliorating/deteriorating items with time-varying demand pattern over a finite planning horizon, taking into account the effects of inflation and time value of money. Optimal solutions of the proposed models are derived and the effects of amelioration/deterioration on the inventory replenishment policies are studied with the help of numerical examples.

How to avoid stockouts when producing several items on a single facility? What to do if you can't?

This paper considers the Multiple Product Single Facility Stockout Avoidance Problem (SAP). That is the problem of determining, given initial inventories, whether there is a multiple product single facility production schedule that avoids stockouts over a given time horizon. The optimization version of the SAP where stockouts are penalized linearly is also studied. We call this problem the Weighted Stockout Problem (WSP). Both problems are NP-hard in the strong sense. Mixed Integer Linear Programming (MIP) formulations for both the SAP and the WSP are developed. We show that there exist polynomial algorithms for some special cases of the SAP and the WSP. We have also developed heuristics and computational results.

Hybrid genetic algorithm for the economic lot-scheduling problem

The economic lot-scheduling problem (ELSP) is an important production scheduling problem that has been intensively studied over 40 years. Numerous heuristic algorithms have been developed since the problem is NP-hard. Dobsons heuristic has been regarded as the best in its performance. The present paper provides a hybrid genetic algorithm based on the time-varying lot sizes approach in the ELSP literature. Numerical experiments show that the hybrid genetic algorithm outperforms Dobsons heuristic.

The multi-item newsvendor problem with a budget constraint and fixed ordering costs

This paper deals with a multi-item newsvendor problem subject to a budget constraint on the total value of the replenishment quantities. Fixed costs for non-zero replenishments have been explicitly considered. Dynamic programming procedures are presented for two situations: (i) where the end item demand distributions are assumed known (illustrated for the case of normally distributed demand) and (ii) a distribution free approach where only the first two moments of the distributions are assumed known. In addition, simple and efficient heuristic algorithms have been developed. Computational experiments show that the performance of the heuristics are excellent based on a set of test problems.

Analytic hierarchy process to assess and optimize distribution network

Effective supply chain distribution network design needs to consider various performance dimensions and product characteristics. Recently, researchers have begun to realize that the decision and integration effort in supply chain design should be driven by a comprehensive set of performance metrics and also product characteristics. In this paper, we relate product characteristics to optimizing supply chain delivery network design and adopt cost and service factor performance metrics as the decision criteria. An analytic hierarchy process (AHP) multi-criteria decision-making methodology is then developed to take into account both qualitative and quantitative factors in the best delivery network design selection. By using AHP methodology we could optimize the selection of delivery network design followed by relevant choices for decision making of Home plus distribution center.

The effects of inflation and time-value of money on an economic order quantity model with a random product life cycle

Abstract For several decades, the Economic Order Quantity (EOQ) model and its variations have received much attention from researchers. Recently, there has been an investigation into an EOQ model incorporating a random product life cycle and the concept of time-value of money. This paper extends the previous research in several areas. First, we investigate the impact of inflation on the choice of replenishment quantities. Second, the unit cost, which has been inadvertently omitted in the previous research, is included in the objective function to properly model the problem. Third, we consider the normal distribution as a product life cycle in addition to the exponential distribution. Fourth, we develop a simulation model which can be used for any probability distribution.

Distribution free procedures for make-to-order (MTO), make-in-advance (MIA), and composite policies

Abstract The purpose of this paper is to study the make-to-order (MTO), make-in-advance (MIA), and composite policies in a single period two echelon stochastic model with more realistic assumptions. We relax the assumption that the cumulative distribution function of demand is completely known and merely assume that its first two moments are known.

The joint replenishment problem with resource restriction

There are many resource restrictions in real production/inventory systems (for example, budget, storage, transportation capacity, etc.). But unlike other research areas, there is very little research to handle the joint replenishment problem (JRP) with resource restriction. The purpose of this paper is to develop two efficient algorithms for solving these problems. Firstly, we modify the existing RAND algorithm to be applicable to the JRP with resource restriction. Secondly, we develop a genetic algorithm for the JRP with resource restriction. Extensive computational experiments are performed to test the performances of the algorithms.