Optimal replenishment policy for imperfect quality EMQ model with rework and backlogging

This paper derives the optimal replenishment policy for imperfect quality economic manufacturing quantity (EMQ) model with rework and backlogging. The classic EMQ model assumes that all items produced are of perfect quality. However, in real‐life manufacturing settings, generation of imperfect quality items is almost inevitable. In this study, a random defective rate is assumed. All items produced are inspected and the defective items are classified as scrap and repairable. A rework process is involved in each production run when regular manufacturing process ends, and a rate of failure in repair is also assumed. Unit disposal cost and unit repairing and holding costs are included in our mathematical modelling and analysis. The renewal reward theorem is employed in this study to cope with the variable cycle length. The optimal replenishment policy in terms of lot‐size and backlogging level that minimizes expected overall costs for the proposed imperfect quality EMQ model is derived. Special cases of the model are identified and discussed. Numerical example is provided to demonstrate its practical usage. Copyright © 2006 John Wiley & Sons, Ltd.     

Notes on the mathematical modeling approach used to determine the replenishment policy for the EMQ model with rework and multiple shipments

A recent article (Chiu et al. (2011) [22]) used mathematical modeling along with differential calculus to derive the optimal replenishment lot size for an economic manufacturing quantity (EMQ) model with rework and multiple shipments. Unlike the conventional method that uses differential calculus with the system cost function to solve the economic lot size problem, this paper proposes a straightforward algebraic approach. It is demonstrated that both the optimal replenishment lot size $Q^1$ and a simplified form for the long-run average cost E[TCU($Q^1$)] for such a specific lot size problem can be derived without using differential calculus. This approach enables practitioners or students who may not have sufficient knowledge of differential calculus to better understand such a practical vendor–buyer integrated system.     

Dynamic lot sizing for multiple products with a new joint replenishment model

This paper studies a new multi-product dynamic lot sizing problem, where the inventories of all products are replenished jointly with the same quantity whenever a production occurs. Such problems may occur in poultry and some chemical industries. We first introduce the general problem that allows for demand rejection with lost sales cost, and prove that the problem is NP-hard. Then we study a special case where all demands have to be satisfied immediately, and show that it can be solved in polynomial time. Finally, we develop two heuristic algorithms for the general problem. Through computational experiments, we demonstrate the effectiveness of the heuristics and investigate some insights related to the decision of lost sales.     

Determining the optimal run time for EPQ model with scrap,rework, and stochastic breakdowns

This paper is concerned with determination of optimal run time for an economic production quantity (EPQ) model with scrap, rework, and stochastic machine breakdowns. In real life manufacturing systems, generation of defective items and random breakdown of production equipment are inevitable. In this study, a portion of the defective items is considered to be scrap, while the other is assumed to be repairable. Total production-inventory cost functions are derived respectively for both EPQ models with breakdown (no-resumption policy is adopted) and without breakdown taking place. These cost functions are integrated and the renewal reward theorem is used to cope with the variable cycle length. Theorems on conditional convexity of the integrated overall costs and bounds of the production run time are proposed and proved. We conclude that the optimal run time falls within the range of bounds and it can be pinpointed by the use of the bisection method based on the intermediate value theorem. Numerical example is provided to demonstrate its practical usages.     

A note on “Determining the optimal run time for EPQ model with scrap,rework, and stochastic breakdowns”

In a recently published paper by Chiu et al. [Chiu, S.W., Wang, S.-L., Chiu, Y.-S.P., 2007. Determining the optimal run time for EPQ model with scrap, rework and stochastic breakdowns. European Journal of Operational Research 180, 664–676], a theorem on conditional convexity of the integrated total cost function was employed in their solution procedure. We reexamine this theorem and present a direct proof to the convexity of the total cost function. This proof can be used in place of Theorem 1 of Chiu et al.’s paper to enhance quality of their optimization process.     

Pricing and lot sizing for an EPQ inventory model with rework and multiple shipments

This paper deals with an economic production quantity (EPQ) inventory model with reworkable defective items when a given multi-shipment policy is used. In this work, it is assumed that in each cycle, the rework process of all defective items starts when the regular production process finishes. After the rework process, a portion of reworked items fails. This portion becomes scrap and only the perfect finished items can be delivered to customers at the end of rework process. A profit function is derived to model the inventory problem and it is shown that the profit function is concave. Due to the complexity of the optimization problem, an algorithm is developed to determine the optimal values of manufacturing lot size and price such that the long-run average profit function is maximized. Furthermore, two special cases are identified and explained. Finally, a numerical example is given to illustrate the applicability of the proposed inventory model.     

Remarks on the optimization method of a manufacturing system with stochastic breakdown and rework process in supply chain management

Chiu et al. (2010) [8] present the proof of convexity of the long-run average cost function E[TCU(t₁)] for a manufacturing system with stochastic breakdown and rework process. This note not only demonstrates that E[TCU(t₁)] is not convex but also adopts the rigorous methods of mathematics to develop the complete solution procedure to find the optimal solution for removing shortcomings of the above paper mentioned.     

Optimal replenishment policy for the EPQ model with permissible delay in payments and allowable shortages

The main purpose of this paper is to investigate the optimal replenishment policy under conditions of permissible delay in payments and allowable shortages within the economic production quantity (EPQ) framework. We extend the work of Chung and Huang [15] to assume that the replenishment rate is finite and the unit selling price is not necessarily equal to the unit purchasing price. A theorem is developed to determine the optimal replenishment policy. Finally, numerical examples are given to illustrate the theorem.     

An optimal replenishment policy for deteriorating items with time-varying demand and partial backlogging

Recently, Papachristos and Skouri developed an inventory model in which unsatisfied demand is partially backlogged at a negative exponential rate with the waiting time. In this article, we complement the shortcoming of their model by adding not only the cost of lost sales but also the non-constant purchase cost.     

An optimal replenishment policy for deteriorating items with effective investment in preservation technology

In this paper, considering the amount invested in preservation technology and the replenishment schedule as decision variables, we formulate an inventory model with a time-varying rate of deterioration and partial backlogging. The objective is to find the optimal replenishment and preservation technology investment strategies while maximizing the total profit per unit time. For any given preservation technology cost, we first prove that the optimal replenishment schedule not only exists but is unique. Next, under given replenishment schedule, we show that the total profit per unit time is a concave function of preservation technology cost. We then provide a simple algorithm to figure out the optimal preservation technology cost and replenishment schedule for the proposed model. We use numerical examples to illustrate the model.     

Multi-tier binary solution method for multi-product newsvendor problem with multiple constraints

This paper considers a multi-product newsvendor problem with multiple constraints. Multiple constraints in the problem make it more challenging to solve. Previous research has attempted to solve the problem by considering two-constraint case or/and using approximation techniques or active sets methods. The solution methods in literature for solving multi-constraint problem are limited or cumbersome. In this paper, by analyzing structural properties of the multi-constraint multi-product newsvendor problem, we develop a multi-tier binary solution method for yielding the optimal solution to the problem. The proposed method is applicable to the problem with any continuous demand distribution and more than two constraints, and its computational complexity is polynomial in the number of products. Numerical results are presented for showing the effectiveness of our method.     

On the convexity for the expected total cost per unit time of the EPQ model with scrap,rework and stochastic machine breakdown

This study explores the economic production quantity model with scrap, rework and stochastic machine breakdown. The main purpose of this paper is twofold:(P1) This paper will adopt the rigorous methods of mathematics to demonstrate that the expected total cost per unit time is convex on all positive numbers to improve the conditional convexity in Theorem 1 of Chiu et al. (2010) [7].(P2) This paper gives the concrete proof to provide bounds for the optimal production run time to remove the logical shortcomings of mathematics presented in proof of Theorem 2 of Chiu et al. (2010) [7].     

An improved algorithm for the minimax distribution-free inventory model with incident-oriented shortage costs

This article reconsiders Gallego's minimax distribution-free procedure. He created a two-point distribution to serve the most unfavorable case for estimating the expected cost of lost sales. We provide a reasonable condition to insure the existence and uniqueness of the optimal solution and the convergence of Gallego's method.     

Retailer’s optimal replenishment and payment policies in the EPQ model under cash discount and two-level trade credit policy

The main purpose of this paper is to investigate the retailer’s optimal cycle time and optimal payment time under the supplier’s cash discount and trade credit policy within the economic production quantity (EPQ) framework. In this paper, we assume that the retailer will provide a full trade credit to his/her good credit customers and request his/her bad credit customers pay for the items as soon as receiving them. Under this assumption, we model the retailer’s inventory system as a cost minimization problem to determine the retailer’s optimal inventory cycle time and optimal payment time under the replenishment rate is finite. Then, an algorithm is established to obtain the optimal strategy. Finally, numerical examples are given to illustrate the theoretical results and obtain some managerial phenomena.     

An instantaneous replenishment model under the effect of a sampling policy for defective items

We propose to study a EOQ-type inventory model with unreliable supply, with each order containing a random proportion of defective items. Every time an order is received, an acceptance sampling plan is applied to the lot, according to which only a sample is inspected instead of the whole lot. If the sample conforms to the standards, i.e. if the number of imperfect items is below an “acceptance number”, no further screening is performed. Otherwise, the lot is subject to 100% screening. We formulate an integer non-linear mathematical program that integrates inventory and quality decisions into a unified profit model, to jointly determine the optimal lot size and optimal sampling plan, characterized by a sample size, and an acceptance number. The optimal decisions are determined in a way to achieve a certain average outgoing quality limit (AOQL), which is the highest proportion of defective items in the outgoing material sold to customers. We provide a counter-example demonstrating that the expected profit function, objective of the mathematical program, is not jointly concave in the lot and sample size. However, we show that for a given sampling plan, the expected profit function is concave in the lot size. A solution procedure is presented to compute the optimal solution. Numerical analysis is provided to gain managerial insights by analyzing the impact of changing various model parameters on the optimal solution. We also show numerically that the optimal profit determined using this model is significantly higher when compared to the optimal profit obtained using Salameh and Jaber (2000)’s [1] model, indicating much higher profits when acceptance sampling is used.     

A continuous review replenishment–disposal policy for an inventory system with autonomous supply and fixed disposal costs

In this study, we analyze an inventory system facing stochastic external demands and an autonomous supply (independent return flow) in the presence of fixed disposal costs and positive lead times under a continuous review replenishment–disposal policy. We derive the analytical expressions of the operating characteristics of the system; and, construct the objective function to minimize the total expected costs of ordering, holding, purchasing and disposal per unit time subject to a fill rate constraint. An extensive numerical analysis is conducted to study the sensitivity of the policy parameters and the benefit of employing a policy which allows for disposal of excess stock in this setting. We model the net demand process as the superposition of normally distributed external demand and inflows, which is expressed as a Brownian motion process. Our findings indicate that the disposal option results in considerable savings even (i) in the presence of non-zero fixed disposal costs, (ii) large actual demand rates with high return ratios (resulting in small net demands) and (iii) for moderate return ratios with high demand variability.     

An optimal replenishment policy for items with inventory-level-dependent demand and fixed lifetime under the LIFO policy

In a recent paper, Hwang and Hahn considered inventory replenishment problems for an item with an inventory-level-dependent demand rate and a fixed lifetime. They developed an EQQ model under the situation of considering the first-in–first-out (FIFO) issuing policy. First, this paper reconsiders Hwang and Hann's problem by employing the last-in–first-out (LIFO) issuing policy, which is more practical in the retail industry. An inventory model is developed. Secondly, the concavity of the objective function is proved. Thirdly, this paper presents conditions where the present model has a unique optimal solution and a method for finding the global optimal solution. A simple solution procedure and sensitivity analyses of parameters are also provided.     

An O(T log T) Algorithm for the Dynamic Lot Size Problem with Limited Storage and Linear Costs

In this paper the dynamic lot size problem with time varying storage capacities and linear costs is addressed. Like in the uncapacitated version, this problem can be formulated as a network flow problem. Considering the properties of the underlying network, we devise an O(T log T) greedy algorithm to obtain optimal policies and we report computational results for randomly generated problems.     

An optimal solution for the stochastic version of the Wagner–Whitin dynamic lot-size model

We present an algorithm for determining the optimal solution over the entire planning horizon for the dynamic lot-size model where demand is stochastic and non-stationary. The optimal solution to the deterministic problem is the well-known Wagner–Whitin algorithm. The present work contributes principally to knowledge building and provides a tool for researchers. One potentially useful contribution to practice is the solution to an important special case, where demand follows normal distributions. Other contributions to practice will likely flow from the development of improved heuristics and the improved basis to evaluate heuristic performance.