Two-echelon stochastic inventory system with returns and partial backlogging

This paper investigates a two-echelon stochastic inventory system with returns and partial backlogging; our proposed model, which is realistic for practical situations, might be applicable in many manufacturing planning situations. The objective is to find a continuous-review inventory control policy that minimises the total expected annual cost of the system. A computer code using the software Mathematica 5.2 is developed to derive the optimal solution. Additionally, we discuss the sensitivity of the optimal solution together with the changes of the values of the parameters associated with the model for decision-making. The results are illustrated with the help of four numerical examples.     

Single period stochastic inventory problems with ordering or returns policies

In recent years, there has been an increasing adoption of returns policies in the coordination of the supply chain, where market demand is always assumed to be satisfied by manufacturing or by ordering from suppliers. However, many industries face the important decision of how to balance their inventory level. This problem has long been studied in financial institutions such as banks. This study presents an optimal inventory policy under a given stochastic demand such as a uniformly distributed demand, single-item, and single period review inventory system. The optimal inventory control policy obtained in this study is called a four-point policy: that is, when the entity’s inventory level is below a reorder point, the entity must increase his stock level by ordering and order up-to a fixed level (second point); when the entity’s inventory level is over a return point (third point); the stock level must be decreased by returns and decreased to a fixed level (fourth point); otherwise, nothing should be done. We also analyze the (K, S)-convex properties of the inventory cost function.     

A single period inventory model with a truncated normally distributed fuzzy random variable demand

In this article, a single period inventory model has been considered in the mixed fuzzy random environment by assuming the annual customer demand to be a fuzzy random variable. Since assuming demand to be normally distributed implies that some amount of demand information is being automatically taken to be negative, the model has been developed for two cases, using the non-truncated and the truncated normal distributions. The problem has been developed to represent scenarios where the aim of the decision-maker is to determine the optimal order quantity such that the expected profit is greater than or equal to a predetermined target. This ‘greater than or equal to’ inequality has been modelled as a fuzzy inequality and a methodology has been developed to this effect. This methodology has been illustrated through a numerical example.     

Two storage inventory model of a deteriorating item with variable demand under partial credit period

In this paper, a two-warehouse inventory model for deteriorating item with stock and selling price dependent demand has been developed. Above a certain (fixed) ordered label, supplier provides full permissible delay in payment per order to attract more customers. But an interest is charged by the supplier if payment is made after the said delay period. The supplier also offers a partial permissible delay in payment even if the order quantity is less than the fixed ordered label. For display of goods, retailer has one warehouse of finite capacity at the heart of the market place and another warehouse of infinite capacity (that means capacity of second warehouse is sufficiently large) situated outside the market but near to first warehouse. Units are continuously transferred from second warehouse to first and sold from first warehouse. Combining the features of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) a hybrid heuristic (named Particle Swarm-Genetic Algorithm (PSGA)) is developed and used to find solution of the proposed model. To test the efficiency of the proposed algorithm, models are also solved using another two established heuristic techniques and results are compared with those obtained using proposed PSGA. Here order quantity, refilling point at first warehouse and mark-up of selling price of fresh units are decision variables. Models are formulated for both crisp and fuzzy inventory parameters and illustrated with numerical examples.     

A single-period inventory and payment model with partial trade credit

In this paper, we consider the ordering and payment issues for a retailer facing stochastic demand. We assume that the retailer can enjoy the partial trade credit from his supplier and borrow money from bank as well if needed, and he can also earn return by investing his superfluous on-hand cash (if any). The retailer’s objective is to maximize the expected cash level at the end of the selling period. We formulate the model of this problem by taking initial inventory and capital levels as the two-dimensional state. First, given the exogenous fraction of immediate payment, we show that unlike the critical fractile solution the retailer’s optimal ordering strategy is a two-threshold policy, which is independent of the retailer’s initial inventory level and capital level. Second, we consider an extensive model where the fraction of immediate payment is decided by the retailer. We employ the sequential optimization procedure to solve the extensive problem, and present the structure of the retailer’s optimal policies under different partial-trade-credit penalty rates. Numerical experiments show that if the fraction of immediate payment is exogenous, both partial trade credit and loan opportunity are detrimental to the capital-constrained retailer in many cases, although they can stimulate the retailer to order more.     

Modeling concurrency with partial orders

Concurrency has been expressed variously in terms of formal languages (typically via the shuffle operator), partial orders, and temporal logic,inter alia. In this paper we extract from these three approaches a single hybrid approach having a rich language that mixes algebra and logic and having a natural class of models of concurrent processes. The heart of the approach is a notion of partial string derived from the view of a string as a linearly ordered multiset by relaxing the linearity constraint, thereby permitting partially ordered multisets orpomsets. Just as sets of strings form languages, so do sets of pomsets form processes. We introduce a number of operations useful for specifying concurrent processes and demonstrate their utility on some basic examples. Although none of the operations is particularly oriented to nets it is nevertheless possible to use them to express processes constructed as a net of subprocesses, and more generally as a system consisting of components. The general benefits of the approach are that it is conceptually straightforward, involves fewer artificial constructs than many competing models of concurrency, yet is applicable to a considerably wider range of types of systems, including systems with buses and ethernets, analog systems, and real-time systems.Revision of Some Constructions for Order-Theoretic Models of Concurrency [Ref. 1].     

一类允许缺货的易变质物品的随机非线性存贮模型

研究了货物存贮问题．考虑到在仓库出空期间一般人们有耐烦与不耐烦两种反应，研究中假设仓库出空期丢失顾客量服从正态分布，据此建立允许缺货的易变质物品的非线性存贮模型，使模型更接近于实际．并给出数值例子，运用Matlab软件求解最优存贮控制策略，得到近似的最佳进货量和最佳出空期长度．     

Two-echelon multi-product multi-constraint product returns inventory model with permissible delay in payments and variable lead time

Supply chain is not limited to delivering products to the end-costumers since the defective products that are returned back to the producers by the consumers. The producers should be superior knowledge to utilize the return products effectively so as to maintain our natural resources and to provide better service to customers. In this paper, a distributor and a warehouse consisting of a serviceable part and a recoverable part supply chain problem is considered in which there are several products, the distributor has limited space capacity and budget to purchase all products. In this supply chain, the defective products are returned back to the warehouse by the distributor and the warehouse recovered those defective products into perfect products having the same value as the procured products. The lead-time of receiving products from a warehouse to a distributor is a variable which is controllable by adding extra crashing cost. For each product, a fraction of the shortage is backordered and the rest are lost. A mathematical model is employed in this study for optimizing the order quantity, lead time and total number of deliveries with the objective of minimizing system total cost. We show that the model of this problem is a constrained non-linear programme and present a simple Lagrangian multiplier technique to solve it. Numerical and sensitivity analysis are given to show the applicability of the proposed model in real-world product returns inventory problems.     

Discovering injective episodes with general partial orders

Frequent episode discovery is a popular framework for temporal pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Currently algorithms exist for episode discovery only when the associated partial order is total order (serial episode) or trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with unrestricted partial orders when the associated event-types are unique. These algorithms can be easily specialized to discover only serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that frequency alone is not a sufficient measure of interestingness in the context of partial order mining. We propose a new interestingness measure for episodes with unrestricted partial orders which, when used along with frequency, results in an efficient scheme of data mining. Simulations are presented to demonstrate the effectiveness of our algorithms.     

An inventory model for deteriorating items with partial backlogging and permissible delay in payments

The paper deals with an inventory model with a varying rate of deterioration and partial backlogging rate under the condition of permissible delay in payments. The existing literature on the subject generally deal with situations where the payment of an order is made on the receipt of items by the inventory system and shortages are either completely backlogged or fully lost. In this paper, a varying deterioration rate of time and the condition of permissible delay in payments used in conjunction with the economic order quantity model are the focus of discussion. In addition, the shortages are neither completely backlogged nor completely lost assuming the backlogging rate to be inversely proportional to the waiting time for the next replenishment. Numerical examples are presented to illustrate the model.