Capacity Pooling Research Articles

협력규칙에 따른 능력공유 시스템 성능분석 모형

협력규칙에 따른 능력공유 시스템 성능분석 모형

Incorporating macroeconomic leading indicators in tactical capacity planning

Tactical capacity planning relies on future estimates of demand for the mid- to long-term. On these forecast horizons there is increased uncertainty that the analysts face. To this purpose, we incorporate macroeconomic variables into microeconomic demand forecasting. Forecast accuracy metrics, which are typically used to assess improvements in predictions, are proxies of the real decision associated costs. However, measuring the direct impact on decisions is preferable. In this paper, we examine the capacity planning decision at plant level of a manufacturer. Through an inventory simulation setup, we evaluate the gains of incorporating external macroeconomic information in the forecasts, directly, in terms of achieving target service levels and inventory performance. Furthermore, we provide an approach to indicate capacity alerts, which can serve as input for global capacity pooling decisions. Our work has two main contributions. First, we demonstrate the added value of leading indicator information in forecasting models, when evaluated directly on capacity planning. Second, we provide additional evidence that traditional metrics of forecast accuracy exhibit weak connection with the real decision costs, in particular for capacity planning. We propose a more realistic assessment of the forecast quality by evaluating both the first and second moment of the forecast distribution. We discuss implications for practice, in particular given the typical over-reliance on forecast accuracy metrics for choosing the appropriate forecasting model.

Capacity Pooling in Hospitals: The Hidden Consequences of Off-Service Placement

Hospital managers struggle with the day-to-day variability in patient admissions to different clinical services, each of which typically has a fixed allocation of hospital beds. In response, many hospitals engage in capacity pooling by assigning patients from a service whose designated beds are fully occupied to an available bed in a unit designated for a different service. This “off-service placement” occurs frequently, yet its impact on patient and operational measures has not been rigorously quantified. This is, in part, because of the challenge of properly accounting for the endogenous selection of off-service patients. We use an instrumental variable approach to quantify the causal effects of off-service placement of hospitalized medical/surgical patients, having accounted for the endogeneity issues. Using data from a large academic medical center with 19.6% of medical/surgical patients placed off service on average, we find that off-service placement is associated with a 22.8% increase in remaining hospital length of stay (LOS) and a 13.1% increase in the likelihood of hospital readmission within 30 days. We find no significant effect on in-hospital mortality or clinical trigger (rapid response) activation. We identify longer distances to the service’s home unit as a key mechanism that drives the effect on LOS. In contrast, a mismatch in nursing specialization does not seem to explain this effect. By quantifying the effects of off-service placement on patient and operational outcomes, we enable clinicians and hospital managers to make better-informed short-term decisions about off-service placement and longer-term decisions about capacity allocation. This paper was accepted by Stefan Scholtes, healthcare management.

Secured information exchange in cloud using cross breed property based encryption

Individuals have the ability to get to the web anyplace and whenever. Distributed computing is an idea that treats the assets on the Internet as a brought together element, to be specific cloud. The server farm administrators virtualized the assets as per the necessities of the clients and uncover them as capacity pools, which the clients can themselves use to store documents or information protest s. Physically, the assets may get put away over numerous servers. Thus, Data heartiness is a noteworthy prerequisite for such stockpiling frameworks. In this paper we have proposed one approach to give information power that is by imitating the message with the end goal that every capacity server stores a duplicate of the message. We have improved the safe distributed storage framework by utilizing a limit intermediary re-encryption strategy. This encryption conspire bolsters decentralized deletion codes connected over scrambled messages and information sending operations over encoded and encoded messages. Our framework is exceedingly dispersed where every capacity server freely encodes and forward messages and key servers autonomously perform incomplete decoding.

Capacity Pooling in Hospitals: The Hidden Consequences of Off-Service Placement

Hospital managers struggle with the day-to-day variability in patient admissions to different clinical services, each of which typically have a fixed allocation of hospital beds. In response, many hospitals engage in capacity pooling by assigning patients from a service whose designated beds are fully occupied to an available bed in a unit designated for a different service. This “off-service placement” occurs frequently, yet its impact on patient and operational measures has not been rigorously quantified. This is, in part, because of the challenge of properly accounting for the endogenous selection of off-service patients. We use an instrumental variable approach to quantify the causal effects of off-service placement of hospitalized medical/surgical patients, having accounted for the endogeneity issues. Using data from a large academic medical center with 19.6 percent of medical/surgical patients placed off service on average, we find that off-service placement is associated with a 22.8 percent increase in remaining hospital length of stay (LOS) and a 13.1 percent increase in the likelihood of hospital readmission within 30 days. We find no significant effect on in-hospital mortality or clinical trigger (rapid response) activation. We identify longer distances to the service’s home unit as a key mechanism that drives the effect on LOS. In contrast, a mismatch in nursing specialization does not seem to explain this effect. By quantifying the effects of off-service placement on patient and operational outcomes, we enable clinicians and hospital managers to make better informed short-term decisions about off-service placement and longer-term decisions about capacity allocation.

Retrial queue with discipline of adaptive permanent pooling

• A single-server retrial queue with novel customer service discipline is introduced and analysed. • Transparent ergodicity condition is derived. • Key performance measures of the system are computed. • Numerical results revealing advantages of the proposed discipline are presented. A novel customer service discipline for a single-server retrial queue is proposed and analysed. Arriving customers are accumulated in a pool of finite capacity. Customers arriving when the pool is full go into orbit and attempt to access the service later. It is assumed that customers access the service as a group. The size of the group is defined by the number of customers in the pool at the instant the service commences. All customers within a group finish receiving the service simultaneously. If the pool is full at the point the service finishes, a new service begins immediately and all customers from the pool begin to be served. Otherwise, the customer admission period starts. The duration of this period is random and depends on the number of customers in the pool when the admission period begins. However, if the pool becomes full before the admission period expires, this period is terminated and a new service begins. The system behaviour is described by a multi-dimensional Markov chain. The generator and the condition of ergodicity of this Markov chain are derived, and an algorithm for computing the stationary probability distribution of the states of the Markov chain is given. Formulas for computing various performance measures of the system are presented, and the results of numerical experiments show that these measures essentially depend on the capacity of the pool and the distribution of the duration of the admission period. The advantages of the proposed customer service discipline over the classical discipline and the discipline in which customers cannot enter the pool during the service period are illustrated numerically.

GI/M/1 type queueing-inventory systems with postponed work, reservation, cancellation and common life time

In this paper we analyze two single server queueing-inventory systems in which items in the inventory have a random common life time. On realization of common life time, all customers in the system are flushed out. Subsequently the inventory reaches its maximum level S through a (positive lead time) replenishment for the next cycle which follows an exponential distribution. Through cancellation of purchases, inventory gets added until their expiry time; where cancellation time follows exponential distribution. Customers arrive according to a Poisson process and service time is exponentially distributed. On arrival if a customer finds the server busy, then he joins a buffer of varying size. If there is no inventory, the arriving customer first try to queue up in a finite waiting room of capacity K. Finding that at full, he joins a pool of infinite capacity with probability γ (0 < γ < 1); else it is lost to the system forever. We discuss two models based on ‘transfer’ of customers from the pool to the waiting room / buffer. In Model 1 when, at a service completion epoch the waiting room size drops to preassigned number L − 1 (1 < L < K) or below, a customer is transferred from pool to waiting room with probability p (0 < p < 1) and positioned as the last among the waiting customers. If at a departure epoch the waiting room turns out to be empty and there is at least one customer in the pool, then the one ahead of all waiting in the pool gets transferred to the waiting room with probability one. We introduce a totally different transfer mechanism in Model 2: when at a service completion epoch, the server turns idle with at least one item in the inventory, the pooled customer is immediately taken for service. At the time of a cancellation if the server is idle with none, one or more customers in the waiting room, then the head of the pooled customer go to the buffer directly for service. Also we assume that no customer joins the system when there is no item in the inventory. Several system performance measures are obtained. A cost function is discussed for each model and some numerical illustrations are presented. Finally a comparison of the two models are made.

Dynamic lead time quotation under responsive inventory and multiple customer classes

We address the lead time quotation problem of a manufacturer serving multiple customer classes. Customers are sensitive to the quoted lead times and the manufacturer has the flexibility to keep inventory to improve responsiveness. We model the problem as a Markov decision process and characterize the optimal lead time quotation, rationing, and production policies. We then define internal and external service level measures and analyze the impact of inventory keeping decision on these measures. Before analyzing the impact, we first derive the relation between inventory level and lead time quotes. We then show that the effect of inventory level on the service levels may not follow the intuition. We also study alternative lead time quotation and production schemes. We contrast the performance of these alternative policies with that of the optimal policy. Specifically, through a numerical study, we quantify the value of controlled arrivals and customer rejection, the value of information on customer status, and the value of a far-sighted policy. Through the numerical study, we also identify the effect of revenue mix and demand mix on the inventory keeping decisions and the performance measures. Finally, we measure the impact of lead time quotation on resource pooling (i.e., inventory and capacity pooling). We show that the value of resource pooling is limited under the optimal policy, since lead time quotation is already effective in balancing the demand with capacity, and in allocating the resources among different customer classes.

Endoscopy by nonphysicians: Conclusions based on faulty data.

Endoscopy by nonphysicians: Conclusions based on faulty data.

Changeable Manufacturing on the Network Level

Agility in the sense of changeability on the manufacturing network level, and here especially the business perspective, has received less attention than the other dimensions of changeability on the lower production levels, as well as in relation to the technological perspective. The present paper aims to enrich the concept of agility in the aforementioned sense, taking strategic management concepts into account that have so far received less attention in relation to changeability. Namely, we consider the concepts of lead factory, capacity pooling and allying, operational flexibility, and the concept of combining products, services and software as fruitful enrichments of the umbrella concept changeability. In so doing, we highlight interdependencies between agility and the analyzed concepts as well as the other changeability dimensions on the lower production level of factories or sites. On this basis, we formulate six hypotheses in consideration of the presented theoretical derivations. Hence, the methodological approach of our research is conceptual and hypothesis generating. Our work is supposed to build the basis for continuative conceptual and empirical research on agility.

A Game for Energy-Aware Allocation of Virtualized Network Functions

Network Functions Virtualization (NFV) is a network architecture concept where network functionality is virtualized and separated into multiple building blocks that may connect or be chained together to implement the required services. The main advantages consist of an increase in network flexibility and scalability. Indeed, each part of the service chain can be allocated and reallocated at runtime depending on demand. In this paper, we present and evaluate an energy-aware Game-Theory-based solution for resource allocation of Virtualized Network Functions (VNFs) within NFV environments. We consider each VNF as a player of the problem that competes for the physical network node capacity pool, seeking the minimization of individual cost functions. The physical network nodes dynamically adjust their processing capacity according to the incoming workload, by means of an Adaptive Rate (AR) strategy that aims at minimizing the product of energy consumption and processing delay. On the basis of the result of the nodes’ AR strategy, the VNFs’ resource sharing costs assume a polynomial form in the workflows, which admits a unique Nash Equilibrium (NE). We examine the effect of different (unconstrained and constrained) forms of the nodes’ optimization problem on the equilibrium and compare the power consumption and delay achieved with energy-aware and non-energy-aware strategy profiles.

Design Incentives Under Collective Extended Producer Responsibility: A Network Perspective

A key goal of Extended Producer Responsibility (EPR) legislation is to provide incentives for producers to design their products for recyclability. EPR is typically implemented in a collective system, where a network of recycling resources are coordinated to fulfill the EPR obligations of a set of producers, and the resulting system cost is allocated among these producers. Collective EPR is prevalent because of its cost efficiency advantages. However, it is considered to provide inferior design incentives compared to an individual implementation (where producers fulfill their EPR obligations individually). In this paper, we revisit this assertion and investigate its fundamental underpinnings in a network setting. To this end, we develop a new biform game framework that captures producers’ independent design choices (noncooperative stage) and recognizes the need to maintain the voluntary participation of producers for the collective system to be stable (cooperative stage). This biform game subsumes the network-based operations of a collective system and captures the interdependence between producers’ product design and participation decisions. We then characterize the manner in which design improvement may compromise stability and vice versa. We establish that a stable collective EPR implementation can match and even surpass an individual implementation with respect to product design outcomes. In particular, we show that when the processing technology efficiency and product recyclability are substitutes (complements), a recycling network where processor capacity pooling leads to sufficiently low (high) cost reduction will lead to superior designs in the collective system and maintain its stability, and we propose cost allocation mechanisms to achieve this dual purpose. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2897 . This paper was accepted by Serguei Netessine, operations management.

Operational hedging strategies and competitive exposure to exchange rates

This paper investigates the impact of operational flexibility on firms׳ economic exposure to currency fluctuations in the presence of global competition. We consider a global firm who sells as a monopolist in the domestic market, and also sells to a foreign market facing competition from a local competitor of certain capacity. We compare the effects of two operational strategies of the global firm, namely, matching currency footprints (“natural hedge”) and the capacity pooling strategy with allocation flexibility. For a two-stage stochastic model, we derive the optimal capacity and selling decisions for the global firm, and from the comparative statics analysis of our model we infer useful managerial insights. (1) We find that operational flexibility enables the global firm to exploit the possible high exchange rate (i.e., devalued home currency) realizations for profit improvement, and thus increases in the long run the firm׳s expected profit. (2) Furthermore, operational flexibility allows for downside risk control as the exchange rate becomes more volatile, since the resource pooling option cleverly exercised minimizes the impact of unfavorable currency realizations. (3) The global firm׳s operational flexibility increases its competitor׳s downside risk, but may also benefit the competitor׳s expected profit since a flexible global firm may decide not to compete when the exchange rate is not favorable. In conclusion, our paper substantiates that “natural hedge” is not effective from a profit maximization perspective. We clearly illustrate the robust profit maximizing performance and reasonable downside risk control of operational hedging approaches, which rely on the clever exercising of operational flexibility options such as resource pooling and allocation, in handling competitive exposure to fluctuating exchange rates.

Agility Enablers in Production Networks – Pooling and Allying of Manufacturing Resources

The organizational structure of a production network holds strong potential to enable agility in manufacturing, if its configuration is expedient. Therefore, this paper explores configurational indicators on production networks. Based on a systematic literature review, 18 articles in 13 peer-reviewed journals are identified. In a three-step approach the implications of different configurational designs on the exploitation and exploration of production network resources are analyzed. The main finding is a different configurational requirement for diverging types of volatility: Market-based volatility requires a redundant network capacity pool, as production shifts and multiple routing can leverage the exploitation of manufacturing resources. Technology-based volatility asks for complementary network capacity, as exploration is increased by a more dynamic distribution of value creation and the built-in real option of innovative resource allocation.

Optimized admission control scheme for coexisting femtocell, wireless and wireline networks

The most important challenge for the implementation of the Future Internet is to make the heterogeneity of access technologies transparent to the end user. Compared to the general case where the interworking networks are independent, the case of femtocells interworking with pre-existing wireless networks poses more challenges due to the sharing of the same backhaul capacity. Therefore, while a user is practically able to initiate the same service through multiple network interfaces, he is allocated capacity from the same capacity pool. However, while the femtocell inherits the QoS mechanisms of cellular networks and is able to provide a reliable CAC, this does not apply to the IP-based networks and that may drastically affect the performance of the femtocell. Hence, we propose an integrated Dynamic Service Admission Control (DSAC) framework for coexisting femtocell, wireless and wireline network environments. In particular, DSAC is able to provide QoS guarantees as a conventional capacity partitioning scheme while at the same time offers better performance in terms of acceptance probability and capacity utilization especially when short term variations of traffic load composition occur.

A fair staff allocation rule for the capacity pooling of multiple call centers

We construct a cooperative staffing game to investigate how to fairly allocate a reduced number of staff among multiple call centers that pool (centralize) their capacities. We show that this game is essential and submodular, and, thereby, convex with a non-empty core. We also propose a neat Shapley value-characterized staff-allocation rule, which exists in the core of the game.

게임상황하에서 Capacity Pooling 효과에 관한 연구

Since pooling is a popular scheme in many areas to attain operational excellence, many researchers investi-gated the performance of pooling systems. However, rare research could be found on pooling with game situation which has much applicability to real world phenomenon. We analyze the performance of non- cooperative pooling system with two servers having different sharing capacity. We investigate the sensiti-vity of the advantage of capacity pooling on the variation of system parameters, including sharing capacity numbers, pooling probability, pooling strategy and traffic intensity. As a result, we suggest an efficient control policy which facilitate the performance of pooling in a game situation.

Advantages of Trichloro Iso Cyanuric Acid over Commercially Available Liquid Chlorine for Sanitation of Swimming Pools in Nagpur Region

This research paper highlights on disinfection and sanitation studies on swimming pools based on several experiments carried out in different swimming pools including water parks in Nagpur and Suburbs. It also suggests practical and effective methods of swimming pool sanitation using TCCA in lieu of existing Liquid chlorine sources. Once implemented, the pool management could have savings potential up to Rs 4,000 per month per ONE Lakh litre capacity pool.

Strategic Investment in Renewable Energy Sources

In this paper we analyze incentives for investment in renewable electricity generating capacity. In particular, we model the tradeoff between investing in a renewable technology (such as wind) and a non-renewable technology (such as natural gas). The renewable technology has higher investment cost and is intermittent-that is, the supply of electricity from this technology is uncertain. The non-renewable technology is reliable and has a lower investment cost, but generation of electricity from this technology entails fuel expenditures as well as emission (carbon) costs. Motivated by existing electricity markets, we model several interrelated contexts, including: (a) vertically integrated electricity supplier, (b) market competition and (c) partial market competition with long-term fixed-price contracts for renewable electricity. Within these contexts we examine the impact of carbon taxes on the total cost and the share of wind capacity in the total capacity portfolio. We nd that intermittency is the critical aspect of renewable technologies which drives the effectiveness of carbon pricing mechanisms. Our results suggest that, due to intermittency of supply and the need for backup generating capacity, increasing the price of carbon emissions may have an unexpected adverse effect on investment in renewables. In addition, we show that market liberalization can have a negative effect on investment in renewable capacity, total cost and total emissions of the system. Fixed price contracts with renewable generators can mitigate these detrimental effects, but they may also lead to excess renewable capacity and insufficient non-renewable capacity in view of their complementary role as backup generators. We conclude that actions towards reducing the intermittency of the renewable energy sources (e.g., through capacity pooling or unit-specific buffering) may be more effective in promoting investment in renewable generation capacity than reliance on carbon taxes alone.

The productivity and cost-efficiency of models for involving nurse practitioners in primary care: a perspective from queueing analysis.

To develop simple stylized models for evaluating the productivity and cost-efficiencies of different practice models to involve nurse practitioners (NPs) in primary care, and in particular to generate insights on what affects the performance of these models and how. The productivity of a practice model is defined as the maximum number of patients that can be accounted for by the model under a given timeliness-to-care requirement; cost-efficiency is measured by the corresponding annual cost per patient in that model. Appropriate queueing analysis is conducted to generate formulas and values for these two performance measures. Model parameters for the analysis are extracted from the previous literature and survey reports. Sensitivity analysis is conducted to investigate the model performance under different scenarios and to verify the robustness of findings. Employing an NP, whose salary is usually lower than a primary care physician, may not be cost-efficient, in particular when the NP's capacity is underutilized. Besides provider service rates, workload allocation among providers is one of the most important determinants for the cost-efficiency of a practice model involving NPs. Capacity pooling among providers could be a helpful strategy to improve efficiency in care delivery. The productivity and cost-efficiency of a practice model depend heavily on how providers organize their work and a variety of other factors related to the practice environment. Queueing theory provides useful tools to take into account these factors in making strategic decisions on staffing and panel size selection for a practice model.