Electronic diary evidence on energy erosion in clinical burnout.

Burnout is generally defined as a state of severe exhaustion. So far, research has predominantly focused on relatively mild burnout in employees able to work despite their complaints. This study examines energy depletion in clinical burnout (e.g., the severest cases on extended sick leave) by comparing the diurnal patterns of fatigue and exhaustion with those of healthy individuals. Sixty clinically burned-out and 40 healthy participants kept an electronic diary for 14 days, 7 times a day, yielding a total of 8,116 diary entries. This study shows that burned-out individuals typically suffer continuously from a severe fatigue throughout the day. The resulting flattened diurnal cycles mark a stable exhaustion that is uncommon in healthy persons. The current results provide novel support for the existence of severe energy erosion in clinical burnout. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An inventory replenishment policy for deteriorating items with shortages and partial backlogging

It has long been assumed that the shortages in inventory systems are either completely backlogged or totally lost. However, it is more reasonable to characterize that the longer the waiting time for the next replenishment, the smaller the backlogging rate would be. Moreover, the opportunity cost due to lost sales should be considered since some customers would not like to wait for backlogging during the shortage periods. Without considering these two realistic conditions, study on the inventory modeling for deteriorating items with shortages and partial backlogging cannot be complete and general. In the present article we define an appropriate time-dependent partial backlogging rate and introduce the opportunity cost due to lost sales. Numerical examples are also presented to illustrate the effects of changes in backlogging parameter and unit opportunity cost on total cost and the optimal number of replenishments.Scope and purposeIn a recent article published in this Journal, Giri et al. (Comput. Oper. Res. 27 (2000) 495–505) implemented an existing procedure to the inventory problem of Hariga and Al-Alyan (Comput. Oper. Res. 24 (1997) 1075–83) which concerns with lot-sizing heuristic for deteriorating items with shortages allowed in all cycles except the last one. Giri et al. deviated from the traditional practice and suggested a new policy allowing shortages in all cycles over a finite planning horizon. Their numerical results indicated the proposed policy is cheaper to operate with a cost reduction up to 15%. However, they did not consider the opportunity cost due to lost sales that happen because customers would not like to wait for backlogging. Moreover, for many products with growing sales, the length of the waiting time for the next replenishment is the main factor for determining whether the backlogging will be accepted or not, and the backlogging rate is expected to be time-dependent. Thus the assumption made in Giri et al. that the backlogging rate is a fixed fraction of the total amount of shortages is not reasonable.The purpose of this paper is to present a more realistic discussion of the inventory problem for deteriorating items with time-varying demands and shortages over a finite planning horizon. In contrast to the model by Giri et al., we define an appropriate partial backlogging rate and introduce the opportunity cost due to lost sales. We attempt to complement their model as a practical and general solution for inventory replenishment problems. With these extensions, the scope of applications of the present results is expanded.     

Stackelberg–Nash equilibrium of pricing and inventory decisions in duopoly supply chains using a nested evolutionary algorithm

Pricing and inventory control in a competing environment, as separate entities, have attracted much attention from academics and practitioners. However, integrating these decisions in a competitive setting has not been significantly analyzed by academics, but is of great significance to practitioners. In this study, the joint decision on price and inventory control of a deterioration product is investigated in a duopoly setting. We consider two competing supply chains, each consisting of one manufacturer and one retailer. Each manufacturer, as the leader of their supply chain determines the wholesale price to maximize their profit, while the retailer as the follower should determine the retail price and inventory cycle to maximize his or her profit. Using a game theoretic approach, we formulate in-chain, and chain-to-chain competition as a bi-level programming problem, and analyze Stackelberg–Nash equilibrium of the problem. Furthermore, two versions of a nested algorithm are proposed to obtain the equilibrium. Both versions employ a modified threshold-accepting (TA) algorithm to solve the first level of the problem. However, while the first version utilizes the modified TA algorithm to deal with the second level of the problem, the second version applies a differential evolution (DE) approach. Eventually, a numerical study is carried out not only to compare two developed versions of the algorithm, but also to implement the sensitivity analysis of main parameters. Based on numerical experiments, although the accuracy of both versions of algorithm are alike, using TA is more computationally efficient than using DE. Furthermore, despite the permissibility of partial backlogging, it has never occurred in equilibrium points due to in-chain and chain-to-chain competition.     

Assessing effect of global inventory planning with enterprise-wide information for a large manufacturer

This paper studies how a global manufacturer with many subsidiaries can achieve enhanced business value for the organization by sharing information within its supply chain network. Specifically, the uncertainties in the demands from the downstream distribution center affect the inventory levels at the upstream distribution center under different inventory policies, considering the uncertain lead times and the given order fill rates. With a generic simulation model and real data, we evaluate the magnitude of savings in inventory under the new inventory policy where information can be shared among subsidiaries, compared to the status quo where subsidiaries run independently with no information sharing. The results show that average inventory level at the upstream DC under the new policy would be reduced by approximately 3%. Considering the given manufacturer's global supply chain distribution network holds about $4 billion in average inventory, the 3% improvement is a very significant savings.     

A maritime inventory routing problem with stochastic sailing and port times

This paper describes a stochastic short sea shipping problem where a company is responsible for both the distribution of oil products between islands and the inventory management of those products at consumption storage tanks located at ports. In general, ship routing and scheduling is associated with uncertainty in weather conditions and unpredictable waiting times at ports. In this work, both sailing times and port times are considered to be stochastic parameters. A two-stage stochastic programming model with recourse is presented where the first stage consists of routing, loading and unloading decisions, and the second stage consists of scheduling and inventory decisions. The model is solved using a decomposition approach similar to an L-shaped algorithm where optimality cuts are added dynamically, and this solution process is embedded within the sample average approximation method. A computational study based on real-world instances is presented.     

Multi-period dynamic supply contracts with cancellation

This paper considers a class of multi-period dynamic supply contracts in which a buyer orders a product from a supplier in each period and the supplier allows the buyer to cancel a portion of an outstanding order with penalty during a planning horizon. We assume that both the buyer and the supplier have common knowledge. We first characterize the buyer's ordering and canceling policy that minimizes his expected cost during the planning horizon. We also characterize the supplier's optimal production policy under a very mild assumption on the costs of production and storage. Based on this structure, we then use simulation to show how the supplier chooses cancellation costs that minimize her expected cost during the planning horizon. Our simulation shows that both the buyer and the supplier would benefit from the contract.     

Multi-product multi-chance-constraint stochastic inventory control problem with dynamic demand and partial back-ordering: A harmony search algorithm

In this paper, a multiproduct inventory control problem is considered in which the periods between two replenishments of the products are assumed independent random variables, and increasing and decreasing functions are assumed to model the dynamic demands of each product. Furthermore, the quantities of the orders are assumed integer-type, space and budget are constraints, the service-level is a chance-constraint, and that the partial back-ordering policy is taken into account for the shortages. The costs of the problem are holding, purchasing, and shortage. We show the model of this problem is an integer nonlinear programming type and to solve it, a harmony search approach is used. At the end, three numerical examples of different sizes are given to demonstrate the applicability of the proposed methodology in real world inventory control problems, to validate the results obtained, and to compare its performances with the ones of both a genetic and a particle swarm optimization algorithms.     

Cost benefits from standardization of the packaging glass bottles

This study deals with a recycling system with two competing brewers. It is assumed that they coordinate their manufacturing operations through standardization of their glass bottles for easy implementation of extended producer responsibility (EPR). Immediate benefits from the standardization are three folds. Firstly, the sorting and exchange processes of the bottles collected for reuse by each brewer become no longer necessary. Secondly, cost reduction is achieved through streamlining of collection and reuse processes. Finally, under the stochastic demand of glass bottles their inventory holding costs and lost sales cost are reduced via inventory pooling. Through the development of the mathematical models we determine an optimal operation policy of the two brewers that maximizes the sum of benefits obtained from standardization. Numerical examples are solved to show the validity of the model. Sensitivity tests are also performed to examine the effects of system parameters on the objective function value and decision variables.     

Robust control strategies for multi-inventory systems with average flow constraints

In this paper, we consider multi-inventory systems in the presence of uncertain demand. We assume that (i) demand is unknown but bounded in an assigned compact set and (ii) the control inputs (controlled flows) are subject to assigned constraints. Given a long-term average demand, we select a nominal flow that feeds such a demand. In this context, we are interested in a control strategy that meets at each time all possible current demands and achieves the nominal flow in the average. We provide necessary and sufficient conditions for such a strategy to exist and we characterize the set of achievable flows. Such conditions are based on linear programming and thus they are constructive. In the special case of a static flow (i.e. a system with 0-capacity buffers) we show that the strategy must be affine. The dynamic problem can be solved by a linear-saturated control strategy (inspired by the previous one). We provide numerical analysis and illustrative examples.     

基于ASP．NET的库存管理系统的研究与开发

高效的库存管理是实现企业信息化中的重要环节。以ASP.NET和SQL Server为技术支持,以B/S模式为架构,用软件工程的指导思想开发库存管理系统。实践证明利用该技术开发的基于Web端的企业库存管理系统简单易用,可以很好的提高企业库存管理的工作效率。