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 Annals of Operations Research   [SJR: 1.186]   [H-I: 78]   [8 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1572-9338 - ISSN (Online) 0254-5330    Published by Springer-Verlag  [2340 journals]
• Computational methods and applications in queueing theory
• Authors: Onno Boxma; Joris Walraevens
Pages: 1 - 2
PubDate: 2017-05-01
DOI: 10.1007/s10479-017-2464-9
Issue No: Vol. 252, No. 1 (2017)

• Analysis of discrete-time queues with general service demands and
finite-support service capacities
• Authors: Michiel De Muynck; Sabine Wittevrongel; Herwig Bruneel
Pages: 3 - 28
Abstract: Abstract In this paper, we study a non-classical discrete-time queueing model with variable service demands and variable service capacities. Specifically, we consider the case where the service capacities of the system, i.e., the numbers of work units that the system can perform during each slot, are independent from slot to slot and have an identical general distribution with finite support. New customers enter the system according to a general independent arrival process. The service demands of the customers, i.e., the numbers of work units of service that each customer requires from the system, are general independent. We present an analytical technique to analyze the behavior of this queueing system. The analysis leads to expressions for the probability generating functions and the moments of the unfinished work in the system, the queueing delay of an arbitrary customer and the number of customers in the system in steady state. We also derive approximations for the tail probabilities of the system content and the customer delay. Numerical results are included to illustrate the impact of the various model parameters on the system performance.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-2060-9
Issue No: Vol. 252, No. 1 (2017)

• Stability criterion of a multiserver model with simultaneous service
• Authors: Alexander Rumyantsev; Evsey Morozov
Pages: 29 - 39
Abstract: Abstract In this paper, we study a multiserver system in which each customer requires a random number of servers simultaneously and a random but identical service time at all occupied servers. This model describes the dynamics of modern high performance clusters. Stability criteria of this system (under exponential assumptions) have been proved earlier for the two-server system only. Using a matrix-analytic approach, we obtain stability criteria of such a system under exponential assumptions and with an arbitrary number of servers.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-1917-2
Issue No: Vol. 252, No. 1 (2017)

• Delay analysis and optimality of the renewal access protocol
• Authors: Yunbae Kim; Ganguk Hwang
Pages: 41 - 62
Abstract: Abstract For many years, the IEEE 802.11 distributed coordination function (DCF) has been widely used as a dominant medium access control (MAC) protocol in wireless networks and a large number of works have been done for analyzing and improving its performance. In our earlier work, as a substitute of the IEEE 802.11 DCF, a simple MAC protocol, called the renewal access protocol (RAP), is proposed. The RAP adopts all of the legacy 802.11 standard but the backoff stage feature. Each terminal selects its backoff counter value from a fixed sized window according to a priori given selection distribution in the RAP, regardless of the packet transmission result. It is shown that, if a Poisson distribution is used as the selection distribution, then the resulting RAP achieves high short-term fairness as well as optimal throughput. In this work, we analyze the relation between delay performance and the selection distribution of the RAP. With the help of effective bandwidth theory, we derive the conditions for the selection distribution of the RAP that optimizes the queue overflow probability. We also construct the delay optimal selection distribution satisfying the optimal conditions for throughput and delay. However, we show that the use of the delay optimal selection distribution results in an extremely slow convergence to steady state compared with that of the Poisson selection distribution. Moreover, we show that the Poisson selection distribution provides near-optimal delay performance. Therefore, we conclude that the use of a Poisson selection distribution is still recommended even from the delay perspective.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-2065-4
Issue No: Vol. 252, No. 1 (2017)

• Staffing of time-varying queues using a geometric discrete time modelling
approach
• Authors: Xi Chen; Dave Worthington
Pages: 63 - 84
Abstract: Abstract Many queueing systems with time-dependent arrivals require time-dependent staffing to provide satisfactory service levels at reasonable cost. Feldman et al. (Manag Sci 54(2):324–338, 2008) proposed an iterative staffing algorithm designed to deliver time-stable performance in which successive iterations were evaluated via simulation experiments. In this paper we present and evaluate an analytical queueing model combined with an iterative staffing algorithm to be used for setting staffing levels to achieve time-stable performance in call centre type queues. Empirical results show that the method to be considerably faster than simulation based methods and considerably more accurate than the industry standard analytical methods.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-2058-3
Issue No: Vol. 252, No. 1 (2017)

• The finite/infinite horizon ruin problem with multi-threshold premiums: a
Markov fluid queue approach
• Authors: Mehmet Akif Yazici; Nail Akar
Pages: 85 - 99
Abstract: Abstract We present a new numerical method to obtain the finite- and infinite-horizon ruin probabilities for a general continuous-time risk problem. We assume the claim arrivals are modeled by the versatile Markovian arrival process, the claim sizes are PH-distributed, and the premium rate is allowed to depend on the instantaneous risk reserve in a piecewise-constant manner driven by a number of thresholds, i.e., multi-threshold premiums. We introduce a novel sample path technique by which the ruin problems are shown to reduce to the steady-state solution of a certain multi-regime Markov fluid queue. We propose to use the already existing numerically efficient and stable numerical algorithms for such Markov fluid queues. Numerical results are presented to validate the effectiveness of the proposed method regarding the computation of the finite- and infinite-horizon ruin probabilities for risk models including those with relatively large number of thresholds.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-2105-0
Issue No: Vol. 252, No. 1 (2017)

• A computational approach to steady-state convergence of fluid limits for
Coxian queuing networks with abandonment
• Authors: Max Tschaikowski; Mirco Tribastone
Pages: 101 - 120
Abstract: Abstract Many-server queuing networks with general service and abandonment times have proven to be a realistic model for scenarios such as call centers and health-care systems. The presence of abandonment makes analytical treatment difficult for general topologies. Hence, such networks are usually studied by means of fluid limits. The current state of the art, however, suffers from two drawbacks. First, convergence to a fluid limit has been established only for the transient, but not for the steady state regime. Second, in the case of general distributed service and abandonment times, convergence to a fluid limit has been either established only for a single queue, or has been given by means of a system of coupled integral equations which does not allow for a numerical solution. By making the mild assumption of Coxian-distributed service and abandonment times, in this paper we address both drawbacks by establishing convergence in probability to a system of coupled ordinary differential equations (ODEs) using the theory of Kurtz. The presence of abandonments leads in many cases to ODE systems with a global attractor, which is known to be a sufficient condition for the fluid and the stochastic steady state to coincide in the limiting regime. The fact that our ODE systems are piecewise affine enables a computational method for establishing the presence of a global attractor, based on a solution of a system of linear matrix inequalities.
PubDate: 2017-05-01
DOI: 10.1007/s10479-016-2193-5
Issue No: Vol. 252, No. 1 (2017)

• Waiting time distributions in an M/G/1 retrial queue with two classes of
customers
• Authors: Bara Kim; Jeongsim Kim
Pages: 121 - 134
Abstract: Abstract We consider an $$\textit{M/G/1}$$ retrial queueing system with two classes of customers, in which the service time distributions are different for both classes of customers. When the server is unavailable, an arriving class-1 customer is queued in the queue with infinite capacity, whereas class-2 customer enters the retrial group. In this paper, we are concerned with the analysis of the waiting time distribution. We obtain the joint transform of the waiting time of a class-2 customer and the number of class-2 customers as well as the Laplace–Stieltjes transform of the waiting time of a class-1 customer. We also obtain all the moments of the waiting time distributions of class-1 and class-2 customers.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-1979-1
Issue No: Vol. 252, No. 1 (2017)

• A simple analysis of the batch arrival queue with infinite-buffer and
Markovian service process using roots method: $$GI ^{[X]}/C$$ G I [ X ] /
C - $$MSP /1/\infty$$ M S P / 1 / ∞
• Authors: M. L. Chaudhry; A. D. Banik; A. Pacheco
Pages: 135 - 173
Abstract: Abstract We consider a batch arrival infinite-buffer single-server queue with generally distributed inter-batch arrival times with arrivals occurring in batches of random sizes. The service process is correlated and its structure is governed by a Markovian service process in continuous time. The proposed analysis is based on roots of the associated characteristic equation of the vector-generating function of system-length distribution at a pre-arrival epoch. We also obtain the steady-state probability distribution at an arbitrary epoch using the classical argument based on Markov renewal theory. Some important performance measures such as the average number of customers in the system and the mean sojourn time have also been obtained. Later, we have established heavy- and light-traffic approximations as well as an approximation for the tail probabilities at pre-arrival epoch based on one root of the characteristic equation. Numerical results for some cases have been presented to show the effect of model parameters on the performance measures.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-2026-y
Issue No: Vol. 252, No. 1 (2017)

• Characterisation of the output process of a discrete-time GI  /  D
/ 1 queue, and its application to network performance
• Authors: Bart Steyaert; Sabine Wittevrongel; Herwig Bruneel
Pages: 175 - 190
Abstract: Abstract In this paper we use the burst factor of a packet stream, which is defined in a general setting, to quantify the long-term variability, or burstiness, of such a stream. We briefly review some existing results to show that this parameter plays an important role in the performance assessment and dimensioning of buffers in network nodes, even in a non-Markovian setting. We then focus on the calculation of this parameter at the egress of a discrete-time GI / D / 1 queueing system, considering different routing scenarios, and show how it can be expressed in terms of the parameters that characterise the arrival process in such a queue. In addition, we demonstrate how these results can be applied to evaluate the buffer performance in the subsequent nodes of a network. The analytic results that are derived throughout this paper are supported by simulations.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-2049-4
Issue No: Vol. 252, No. 1 (2017)

• Moments of losses during busy-periods of regular and nonpreemptive
oscillating $$M^X/G/1/n$$ M X / G / 1 / n systems
• Authors: Fátima Ferreira; António Pacheco; Helena Ribeiro
Pages: 191 - 211
Abstract: Abstract This work addresses loss characteristics associated to busy-periods of regular and nonpreemptive oscillating $$M^X/G/1/n$$ systems. By taking advantage of the Markov regenerative structure of the number of customers in the system and resorting to results on moments of compound mixed Poisson distributions, it proposes a fast and easy to implement recursive procedure to compute integer moments of the number of customers lost in busy-periods initiated with multiple customers in the system.
PubDate: 2017-05-01
DOI: 10.1007/s10479-015-1901-x
Issue No: Vol. 252, No. 1 (2017)

• Model and metaheuristics for a scheduling problem integrating procurement,
sale and distribution decisions
• Authors: Simon Thevenin; Nicolas Zufferey; Rémy Glardon
Abstract: Abstract This paper presents an integrated approach for short-term supply chain management (SCM) at a fast moving consumer goods production plant. The problem is to determine the production quantities, to provide a detailed production schedule, to trigger the relevant express deliveries of raw material, and to manage the distribution. We propose a linear integer model, which integrates all of these decisions within scheduling. To find high quality solutions in a reasonable amount of time, various solution methods are proposed, such as a greedy constructive heuristic, two tabu search metaheuristics, a basic variable neighborhood search and an enhanced one, which uses a variable shaking operator. Experiments on realistic instances show that the latter method is efficient and robust. This paper is a contribution to the SCM literature (indeed, only few references address the integration of short term decisions) and to the general metaheuristics field (as the variable neighborhood search paradigm is extended).
PubDate: 2017-04-26
DOI: 10.1007/s10479-017-2498-z

• An extension on super slacks-based measure DEA approach
• Authors: Ya Chen; Yongjun Li; Liang Liang; Huaqing Wu
Abstract: Abstract In order to break the tie of efficient decision-making units, super-efficiency data envelopment analysis is proposed to fully discriminate them. Recently, a slacks-based version of the super slacks-based measure (S-SBM) is developed and a novel two-stage approach is proposed to calculate both super-efficiency score by the S-SBM model and efficiency score by the slacks-based measure model. In this paper, we extend the approach to consider continuity of efficiency scores. We illustrate the discontinuity of efficiency measure, and define a continuous slacks-based measure which is proved continuous and directly calculated. An interesting efficiency zone category is also provided. In addition, this paper investigates the relationship among the super-efficiency measures of the proposed approach and some existing approaches under variable returns to scale.
PubDate: 2017-04-19
DOI: 10.1007/s10479-017-2495-2

• Decomposition method for oligopolistic competitive models with common
environmental regulation
• Authors: E. Allevi; A. Gnudi; I. V. Konnov; G. Oggioni
Abstract: Abstract Global climate change has encouraged international and regional adoption of environmental policies aiming at reducing the generation of greenhouse gas emissions. Europe has taken the leadership in environmental regulations by introducing the European-Union Emissions Trading System (EU-ETS) in 2005 and other policies to mitigate carbon emissions and increase the efficiency of production processes. These environmental policies have significantly affected the production choices of the European energy and industrial sectors. In this paper, we consider a market where a set of players (firms) produce different commodities under a common environmental regulation that limits their emissions. Due to these environmental restrictions, the problem is treated as a generalized non-cooperative game where players have joint (environmental) constraints caused by the common and compulsory emission regulation. The problem is to find a natural mechanism for attaining the corresponding generalized equilibrium state. We suggest a share allocation method, which yields a suitable decomposition type procedure and replaces the initial problem with a sequence of non-cooperative games on Cartesian product sets. We also show that its implementation can be simplified essentially after the application of a regularized penalty method. In the case study, we take inspiration from the EU-ETS and we introduce an environmental regulation that restricts the carbon emissions of firms representing the energy, cement, and steel sectors respectively in Germany, France, Italy, and Spain. Our results confirm the important role played by energy sector in reducing carbon emissions.
PubDate: 2017-04-18
DOI: 10.1007/s10479-017-2494-3

• Reverse auctions with regret-anticipated bidders
• Authors: Xiaohu Qian; Shu-Cherng Fang; Min Huang; Qi An; Xingwei Wang
Abstract: Abstract Suppliers may experience emotional/behavioral consequences of anticipated regrets that consist of winner and loser regrets in first- and second-price sealed-bid reverse auctions. Constructing mathematical models that incorporate regret theory to derive closed-form solutions of regret-anticipated suppliers’ bid decisions, this paper theoretically examines the effects of anticipated regrets on suppliers’ bid prices, buyer’s expected procurement cost and auction format decision. Comparing with the no regret scenario, we find that winner regret has adverse effects on the buyer’s expected procurement cost in first-price sealed-bid reverse auctions with regret-anticipated suppliers. To mitigate the adverse effects, we propose using the reserve price strategy for the buyer with theoretical analysis and numerical supports. An interesting analysis reveals that as the number of suppliers increases, the optimal reserve price increases or decreases depending on the degree of winner regret is lower or higher than that of loser regret. Also, the classical revenue equivalence theorem no longer holds when the degree of winner regret differs from that of loser regret.
PubDate: 2017-04-11
DOI: 10.1007/s10479-017-2475-6

• Improving hospital layout planning through clinical pathway mining
• Authors: Ines Verena Arnolds; Daniel Gartner
Abstract: Abstract Clinical pathways (CPs) are standardized, typically evidence-based health care processes. They define the set and sequence of procedures such as diagnostics, surgical and therapy activities applied to patients. This study examines the value of data-driven CP mining for strategic healthcare management. When assigning specialties to locations within hospitals—for new hospital buildings or reconstruction works—the future CPs should be known to effectively minimize distances traveled by patients. The challenge is to dovetail the prediction of uncertain CPs with hospital layout planning. We approach this problem in three stages: In the first stage, we extend a machine learning algorithm based on probabilistic finite state automata (PFSA) to learn significant CPs from data captured in hospital information systems. In that stage, each significant CP is associated with a transition probability. A unique feature of our approach is that we can generalize the data and include those CPs which have not been observed in the data but which are likely to be followed by future patients according to the pathway probabilities obtained from the PFSA. At the same time, rare and non-significant CPs are filtered out. In the second stage, we present a mathematical model that allows us to perform hospital layout planning decisions based on the CPs, their probabilities and expert knowledge. In the third stage, we evaluate our approach based on different performance measures. Our case study results based on real-world hospital data reveal that using our CP mining approach, distances traveled by patients can be reduced substantially as compared to using a baseline method. In a second case study, when using our approach for reconstructing a hospital and incorporating expert knowledge into the planning, existing layouts can be improved.
PubDate: 2017-04-09
DOI: 10.1007/s10479-017-2485-4

• Risk minimization in multi-factor portfolios: What is the best
strategy?
• Authors: Philipp J. Kremer; Andreea Talmaciu; Sandra Paterlini
Abstract: Abstract Exposures to risk factors, as opposed to individual securities or bonds, can lead to an ex-ante improved risk management and a more transparent and cheaper way of developing active asset allocation strategies. This paper provides an extensive analysis of eight state-of-the-art risk-minimization schemes and compares risk factor performance in a conditional performance analysis, contrasting good and bad states of the economy. The investment universe spans a total of 25 risk factors, including size, momentum, value, high profitability and low investments, from five non-overlapping regions (i.e., USA, UK, Japan, Developed Europe ex. UK and, Asia ex. Japan). Considering as investment period the interval from May 2004 to June 2015, our results show that each single factor yields positive premia in exchange for risk, which can lead to considerable underperformance and extensive recovery periods during times of crisis. The best factor investments can be found in Asia ex. Japan and the US. However, risk factor based portfolio construction across the various regions enables the investor to exploit low correlation structures, reducing the overall volatility, as well as tail- and extreme risk measures. Finally, the empirical results point towards the long-only global minimum variance portfolio, as the best risk minimization strategy.
PubDate: 2017-04-07
DOI: 10.1007/s10479-017-2467-6

• Bridging the research-practice gap in disaster relief: using the IFRC Code
of Conduct to develop an aid model
• Authors: John B. Coles; Jing Zhang; Jun Zhuang
Abstract: Abstract Bridging the gap between research and practice has been a recognized problem in many fields, and has been especially noticeable in the field of disaster relief. As the number and impact of disasters have increased, there has been a jump in interest from the research community in an attempt to provide tools and solutions for some of the challenges in the field. The International Federation of Red Cross and Red Crescent Societies (IFRC) Code of Conduct (CoC) for Disaster Operations provides a qualitative set of guidelines that is an excellent building block for operational theory, but is insufficiently rigorous in guiding quantitative decision making. In this paper, we review the CoC, exploring each of the ten core principles and identifying three significant operational trade-offs. We then propose a model framework that can be implemented as a stand-alone model, or can be used as a foundation for other quantitative aid allocation models. Finally, we provide an example of how the proposed model could be used to guide decision making in a Microsoft Excel $$^{{\textregistered }}$$ environment using CoinOR’s OpenSolver $$^{\textregistered }$$ . New insights in the field of aid disbursement are provided by examining the challenges of financial management and investment as dictated by the CoC. This paper fills a unique gap in the literature by addressing the issue of financial allocation as guided by a qualitative standard used by the disaster relief community, and serves as a complement to the work in the field of humanitarian logistics.
PubDate: 2017-04-06
DOI: 10.1007/s10479-017-2488-1

• A service model for nutrition supplement prediction based on Fuzzy Bayes
model using bigdata in livestock
• Authors: Saraswathi Sivamani; Jongsun Choi; Yongyun Cho
Abstract: Abstract The paper proposes a novel method in the decision support system for the nutritional management of livestock using the Bayesian model based on fuzzy rules. The objective is to analysis the decision based on fuzzy rules over the nutrition management that helps to improve the health of the livestock. Bayesian logic mainly focuses on the probabilities of the food intake with respect to the Food Intake Amount, Cow Stage and weight of the livestock. The conditional probability of the Bayesian reasoning is introduced along with the fuzzy rule, to determine the health status of the livestock. The fuzzy logic technique helps to decide on the decision system, when there are more than one dependencies. In this paper, the total digestible nutrient of the cow is determined over the period of time to get the rate of probability, and the fuzzy rule is applied to determine the health status of the cow, to predict the nutritional intake in the livestock.
PubDate: 2017-04-04
DOI: 10.1007/s10479-017-2490-7

• Two-warehouse inventory model for non-instantaneous deteriorating items
with stock-dependent demand and inflation using particle swarm
optimization
• Authors: Sunil Tiwari; Chandra K. Jaggi; Asoke Kumar Bhunia; Ali Akbar Shaikh; Mark Goh
Abstract: Abstract We investigate a two-warehouse inventory model for non-instantaneous deteriorating items with partial backlogging and stock-dependent demand under inflationary conditions. Shortages are allowed. The backlogging rate is variable and depends on the waiting time for the next replenishment. This paper seeks to determine an optimal replenishment policy that minimizes the present value of the total cost per unit time. The necessary and sufficient conditions for the existence and uniqueness of the optimal solution are found. The corresponding problems are formulated and solved with particle swarm optimization. Numerical experimentation and post-optimality analysis are conducted.
PubDate: 2017-04-04
DOI: 10.1007/s10479-017-2492-5

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