Demand Classes Research Articles

Concepto de conflicto armado interno y seguridad jurídica

<p>El legislador colombiano del año 2000, al momento de elaborar el código penal que en la actualidad rige, creó un nuevo bien jurídico, el cual fue ubicado en el Título II de la parte especial del cuerpo normativo mencionado, bajo la denominación de “Delitos contra Personas y Bienes Protegidos por el Derecho Internacional Humanitario”. En tal sentido, se debe entender que las conductas ubicadas en esta parte del código penal se dirigen a proteger de manera prevalerte los valores que inspiran el cuerpo normativo conocido como Derecho Internacional Humanitario. Así, en caso de ocurrir la muerte de una persona internacionalmente protegida, se debe entender que el castigo que se imponga por tal hecho no sólo busca reivindicar el derecho a la vida de la víctima, sino que, además, necesariamente debe hacerse un reconocimiento expreso de la vigencia y el respeto debido a los intereses protegidos por el derecho humanitario, tal como lo es el principio de distinción, pues de lo contrario no existiría razón alguna para que el legislador hubiese creado esta clase de conductas punibles, si no es precisamente porque se dirigen a la preservación de un bien jurídico nuevo entre nosotros, como lo es el de los altos intereses que sustentan al Derecho Internacional de los Conflictos Armados.</p><p>Ahora bien, para que los delitos ubicados en el Título II de la parte especial del código penal puedan ser aplicados, requieren que se de la presencia de un elemento normativo jurídico del tipo, cual es la existencia de una situación que pueda ser calificada como conflicto armado, para el caso colombiano, tendrá que revestir el carácter de interno. Lo anterior en la medida en que esta clase de tipos penales exigen que la conducta se desarrolle con ocasión o en desarrollo de conflicto armado.</p><p>Siendo que se trata de un elemento normativo, de carácter jurídico, en Colombia no existe acuerdo sobre la existencia o no de una situación que pueda ser calificada como conflicto armado interno, puesto que el poder ejecutivo lo niega, mientras que otros lo afirman. La anterior situación genera una grave situación de inseguridad jurídica, puesto que el operador de justicia se verá enfrentado a diversas interpretaciones, algunas de ellas de contenido político, que de manera necesaria influirán en la decisión a tomar respecto a cuál delito aplicar, si uno contra persona o bien internacionalmente protegido, o por el contrario acudir al resto del catálogo de delitos que se cometen en estado de normalidad.</p><p>Siendo un tema de interpretación jurídica, corresponde al operador de justicia realizar la labor hermenéutica, acudiendo para ello a las fuentes jurídicas con las que cuenta, para el caso la normatividad que define qué se debe entender por conflicto armado interno.</p>

The Image Containment Problem and Some Classes of Polynomial Instances

The image containment problem (ICP) is a minimum cost design problem concerning the containment of particular polyhedra, called zonotopes, that are images of boxes through linear transformations. The ICP is NP‐hard. Here we study a family of nontrivial ICP instances, called worst case demand (WCD) instances. We prove that such instances can be recognized and solved in polynomial time via linear programming. Then we characterize the classes of instances that are WCD independently on the choice of the cost vector (structurally worst case demand classes (SWCD)) and we show that recognizing whether a class of instances is SWCD is a coNP‐complete problem. Finally, we describe two families of SWCD classes that are interesting from an applicative point of view: the classes defined by the incidence matrices of particular directed graphs and those defined by pre‐Leontief matrices.

Production and Inventory Control of a Single Product Assemble-to-Order System with Multiple Customer Classes

We consider the optimal production and inventory control of an assemble-to-order system with m components, one end-product, and n customer classes. A control policy specifies when to produce each component and, whenever an order is placed, whether or not to satisfy it from on-hand inventory. We formulate the problem as a Markov decision process and characterize the structure of an optimal policy. We show that a base-stock production policy is optimal, but the base-stock level for each component is dynamic and depends on the inventory level of all other components (more specifically, it is nondecreasing). We show that the optimal inventory allocation for each component is a rationing policy with different rationing levels for different demand classes. The rationing levels for each component are dynamic and also nondecreasing in the inventory level of all other components. We compare the performance of the optimal policy to heuristic policies, including the commonly used base-stock policy with fixed base-stock levels, and find them to perform surprisingly well, especially for systems with lost sales.

An evaluation of the middleware’s impact on the performance of object oriented distributed systems

In this paper, we present a performance analysis of the response time of a client–server e-banking application running over three different enterprise middleware platforms, namely HTTPServlets, RMI and Web services with JAX-RPC. We conducted performance testing with the purpose to reveal the specific characteristics of each middleware technology and the impact that they infer on the distributed application’s performance. A server node running the three J2EE platforms was benchmarked over a wide array of intranet usage patterns. A statistical analysis of the collected data led into conclusions regarding the benefits of each middleware technology. The simulation framework can be further extended to become a testing tool able to differentiate on various service demand classes as an input in distributed applications so as to offer first-cut validated results concerning the systems’ performance.

Supply chain inventory optimization with two customer classes in discrete time

In this paper we consider a single-item inventory system where two demand classes with different service requirements are satisfied from a common inventory. A critical level, reorder point, order quantity or ( s, q, k) policy is in use. The time axis is divided into discrete time units, which is a common characteristic of many real-life supply-chain processes. The inventory process within the lead time of a replenishment order is modelled as a sequence of (1) an ordinary renewal process and (2) two alternating renewal processes. Approximations are developed for the demand class-specific fill rates and the probability distribution of the waiting time of low priority customer orders. This waiting time distribution is used for the inventory allocation in a two-stage supply chain.

Cost optimization in the [formula omitted] lost sales inventory model with multiple demand classes

For the ( S - 1 , S ) lost sales inventory model with multiple demand classes that have different lost sales penalty cost parameters, three accurate and efficient heuristic algorithms are presented that, at a given base stock level, aim to find optimal values for the critical levels, i.e., values that minimize inventory holding and penalty cost.

Large newsvendor games

We consider a game, called newsvendor game, where several retailers, who face a random demand, can pool their resources and build a centralized inventory that stocks a single item on their behalf. Profits have to be allocated in a way that is advantageous to all the retailers. A game in characteristic form is obtained by assigning to each coalition its optimal expected profit. We consider newsvendor games with possibly an infinite number of newsvendors. We prove in great generality results about balancedness of the game, and we show that in a game with a continuum of players, under a nonatomic condition on the demand, the core is a singleton. For a particular class of demands we show how the core shrinks to a singleton when the number of players increases.

Priority and dynamic scheduling in a make‐to‐stock queue with hyperexponential demand

AbstractWe consider the scheduling problem in a make‐to‐stock queue with two demand classes that can be differentiated based on their variability. One class experiences Poisson arrivals and the other class experiences hyperexponential renewal arrivals. We provide an exact analysis of the case where the demand class with higher variability is given non‐preemptive priority. The results are then used to compare the inventory cost performance of three scheduling disciplines, first‐come first‐serve and priority to either class. We then build on an existing dynamic scheduling heuristic to propose a modification that works well for our system. Extensions of the heuristic to more than two classes and to the case where demand state is known are also discussed. © 2006 Wiley Periodicals, Inc. Naval Research Logistics, 2006.

An [formula omitted] Markovian inventory system with lost sales and two demand classes

In this article a lost sales ( s , Q ) inventory system with two types of customers viz. ordinary and priority customers and exponentially distributed leadtimes is analyzed. Demands from each type of customer arrive according to two independent Poisson processes with different parameters. The expression for the long-run expected cost rate is derived. A computationally efficient algorithm for determining the optimal values for reorder level and reorder quantity is developed.

Resource Flexibility with Responsive Pricing

This article studies two types of flexibility used by firms to better respond to uncertain market conditions: resource flexibility and responsive pricing. We consider a situation in which a single flexible resource can be used to satisfy two distinct demand classes. While the resource capacity must be decided based on uncertain demand functions, the resource allocation as well as the pricing decision are made based on the realized demand functions. We characterize the effects of two key drivers of flexibility: demand variability and demand correlation, assuming normally distributed demand curve intercepts. Demand variability creates opportunity costs and, with fixed prices, decreases the firm’s profit. We show that with the additional flexibility gained from responsive pricing, the firm can maximize the benefits of favorable demand conditions and mitigate the effects of poor demand conditions, ultimately profiting from variability. Positive demand correlation, on the other hand, remains undesirable under responsive pricing. The optimal capacity of the flexible resource is always increasing in both demand variability and demand correlation. This contrasts with the scenarios based on fixed prices, highlighting the crucial difference that responsive pricing makes in the management of flexible resources. We further quantify the value of flexibility for the firm and its customers by considering, as a benchmark, a firm relying on two dedicated resources. The value of flexibility is most significant if the demand levels are highly variable and negatively correlated. In such cases, the firm benefits from demand variability due to responsive pricing, while facing limited demand risk due to resource flexibility. Finally, we endogenize the input price of the flexible resource by considering the pricing decision of the resource supplier.

A Single-Product Inventory Model for Multiple Demand Classes

We consider a single-product inventory system that serves multiple demand classes, which differ in their shortage costs or service-level requirements. We assume a critical-level control policy, and a backorder clearing mechanism in which we treat a backorder for a lower-priority class equivalent to a reserve-stock shortfall for the higher-priority class. We show the equivalence between this inventory system and a serial inventory system. Based on this equivalence, we develop a model for cost evaluation and optimization under the assumptions of Poisson demand, deterministic replenishment lead time, and a continuous-review (Q, R) policy with rationing. We propose a computationally efficient heuristic and develop a bound on its performance. We provide a numerical experiment to show the effectiveness of the heuristic and the value from a rationing policy. Finally, we describe how to extend the model to permit service times, and how to extend the model to a multi-echelon setting.

Inventory Sharing and Rationing in Decentralized Dealer Networks

An increasing number of manufacturers have started to pursue a strategy that promotes inventory sharing among the dealers in their distribution network. In this paper we analyze a decentralized dealer network in which each independent dealer is given the flexibility to share his inventory. We model inventory sharing as a multiple demand classes problem in which each dealer faces his own customer demand with high priority, and inventory-sharing requests from other dealers with low priority. Assuming that each dealer uses a base-stock and threshold-rationing policy for his inventory-stocking and inventory-sharing decisions, we explicitly model the interactions between the dealers through inventory sharing and obtain a closed-form cost function for each dealer based on the steady-state distribution of the inventory levels at the two dealers. We then provide a detailed supermodularity analysis of the inventory-sharing and inventory-rationing game in which each dealer has a two-dimensional strategy set (stocking level and rationing level). We show that the full-sharing game (in which dealers precommit to sharing all of their on-hand inventory) and the fixed-sharing-level game (in which dealers precommit to sharing a portion of their on-hand inventory) are supermodular, and thus a pure-strategy Nash equilibrium is guaranteed to exist. For the rationing game (in which dealers precommit to their stocking levels), we show that there exists a dominant strategy equilibrium on the dealers’ sharing (rationing) levels. Finally, a comprehensive computational study is conducted to highlight the impact of the manufacturer’s incentives, subsidies, and/or transshipment fees on the dealers’ sharing behavior.

A Single-Product Inventory Model for Multiple Demand Classes

We consider a single-product inventory system that serves multiple demand classes, which differ in their shortage costs or service level requirements. We assume a critical-level control policy, and show the equivalence between this inventory system and a serial inventory system. Based on this equivalence, we develop a model for cost evaluation and optimization, under the assumptions of Poisson demand, deterministic replenishment lead-time, and a continuous-review (Q, R) policy with rationing. We propose a computationally-efficient heuristic and develop a bound on its performance. We provide a numerical experiment to show the effectiveness of the heuristic and the value from a rationing policy. Finally, we describe how to extend the model to permit service times, and to embed within a multi-echelon setting.

Optimal Policies for Inventory Systems with Priority Demand Classes

We consider a periodic review inventory system with two priority demand classes, one deterministic and the other stochastic. The deterministic demand must be met immediately in each period. However, the units of stochastic demand that are not satisfied during the period when demand occurs are treated as lost sales. At each decision epoch, one has to decide not only whether an order should be placed and how much to order, but also how much demand to fill from the stochastic source. The firm has the option to ration inventory to the stochastic source (i.e., not satisfy all customer demand even though there is inventory in the system). We first characterize the structure of the optimal policy. We show that, in general, the optimal order quantity and rationing policy are state dependent and do not have a simple structure. We then propose a simple policy, called (s, k, S) policy, where s and S (ordering policy) determine when and how much to order, while k (rationing policy) specifies how much of the stochastic demand to satisfy. We report the results of a numerical study, which shows that this simple policy works extremely well and is very easy to compute.

A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes

Motivated by a study of the logistics systems used to manage consumable service parts for the U.S. military, we consider a static threshold-based rationing policy that is useful when pooling inventory across two demand classes characterized by different arrival rates and shortage (stockout and delay) costs. The scheme operates as a (Q, r) policy with the following feature. Demands from both classes are filled on a first-come-first-serve basis as long as on-hand inventory lies above a threshold levelK. Once on-hand inventory falls below this level, low-priority (i.e., low shortage cost) demand is backordered while high-priority demand continues to be filled. We analyze this static policy first under the assumption that backorders are filled according to a special threshold clearing mechanism. Structural results for the key performance measures are established to enable an efficient solution algorithm for computing stock control and rationing parameters (i.e.,Q, r, andK). Numerical results confirm that the solution under this special threshold clearing mechanism closely approximates that of the priority clearing policy. We next highlight conditions where our policy offers significant savings over traditional “round-up” and “separate stock” policies encountered in the military and elsewhere. Finally, we develop a lower bound on the cost of the optimal rationing policy. Numerical results show that the performance gap between our static threshold policy and the optimal policy is small in environments typical of the military and high-technology industries.

A fuzzy mid-term single-fab production planning model

Production planning is a complicated task for a semiconductor fabrication plant because of the uncertainties in demand, product prices, cycle times, and product yields. Traditionally, mid-term production planning for a semiconductor fabrication plant is handled with MRP systems or optimized by solving LP or FLP problems. In this study, the philosophy of prioritizing demand classes with higher certainties as proposed by Leachman (1993) is applied to the FLP model of Chen and Wang (1998), and a new FLP model for planning the mid-term production of single wafer fabrication plant is constructed. Parameters in this model are given in the form of trapezoidal fuzzy numbers. Fuzzy comparison is adopted in dealing with the fuzzy objective function and expanding inequalities. The outputs are projected using Chen and Wang's fuzzy dynamic production function. The uncertain demand is classified and satisfied with four successively optimized FLP submodels according to their ascending uncertainties. Chen and Wang's example is adopted to demonstrate the proposed methodology and to make some comparisons. By moving more capacity to demand classes with higher certainties that are usually nearer and have larger discounted revenues, the proposed methodology achieves a higher value of the discounted cash flows than the two referenced models.

Dynamic rationing policies for product with incremental upgrading demands

In environments in which several distinct classes of demand exist for a fixed number of a perishable product and backlogging is not allowed, the total sales revenue depends on the sales number for each demand-class. In such environments it is important to establish a rationing policy that provides decision rules for accepting or denying individual requests during the entire planning period. Thus, a dynamic rationing policy is proposed to meet the situation wherein a significant number of rejected customers are expected to sequentially request the next higher-fare demand-class. The proposed dynamic rationing policy has the ability to revise decision rules according to the actual selling status over the entire planning period.

INVENTORY RATIONING AND SHIPMENT FLEXIBILITY ALTERNATIVES FOR DIRECT MARKET FIRMS

This paper investigates inventory‐rationing policies of interest to firms operating in a direct market channel. We model a single product with two demand classes, where one class requests a lower order fulfillment lead time but pays a higher price. Demand for each class follows a Poisson process. Inventory is fed by a production system with exponentially distributed build times. We study rationing policies in which the firm either blocks or backlogs orders for the lower priority customers when inventory drops below a certain level. We compare the performance of these rationing policies with a pure first‐come, first‐serve policy under various scenarios for customer response to delay: lost sales, backlog, and a combination of lost sales and backlog.

Restricted time-remembering policies for the inventory rationing problem

We analyse an ( s, Q) inventory model with unit Poisson demand, several demand classes and lost sales. When dealing with different demand classes the usual approach is to control the inventory by critical levels at which stock is reserved for demand of higher priority. We focus on time-remembering policies where the critical levels are allowed to depend on the time since the actual outstanding order (if any) was issued. In particular, we introduce a new class of policies called restricted time-remembering (RTR) policies. We divide the lead time in m intervals of time and restrict the critical levels of the RTR policy to be constant over each interval of time. This policy is much easier to implement than the optimal rationing policy, where the critical levels can change continuously over time, and in a numerical study we show that the performance of the RTR policy is close to that of the optimal policy, even when the number of intervals is 2 or 3.

A continuous time inventory model for a product recovery system with multiple options

Increasing environmental consciousness, limited availability of natural resources to manufacture new products, recovery quotas to avoid disposal, manufacturers assigned to be responsible for used products, and materials value of components included in returned products are incentives for product recovery. The fact that we now have two possible sources to service demand raises new operational questions. For instance, when is remanufacturing of used and returned products preferred to producing the requirements. Most production and inventory management models for reverse logistics are restricted to stationary demands and returns and do not address seasonal effects and product life cycles. Therefore, we consider a deterministic model with dynamic demands and returns. Then there might exist time periods where returns exceed demands and vice versa. The question has to be answered whether excess returns should be stored for future recovery or disposed of. In our work, there are different demand classes, e.g. different product qualities or different markets. This adds yet another aspect to be examined. It has to be determined for which demand class returns should be used. As a result returns can either be stored for later use for a certain demand class or being used instantly for another class. Demands have to be satisfied either from production or remanufacturing of returned products and returns not needed for recovery may be disposed of. In this paper we determine the optimal production, remanufacturing, and disposal policy for a linear cost model by applying Pontryagin's Maximum Principle.