Gabor analysis over finite Abelian groups

Gabor frames for signals over finite Abelian groups, generated by an arbitrary lattice within the finite time–frequency plane, are the central topic of this paper. Our generic approach covers both multi-dimensional signals as well as non-separable lattices, and in fact the multi-window case as well. Our generic approach includes most of the fundamental facts about Gabor expansions of finite signals for the case of product lattices, as they have been given by Qiu, Wexler–Raz or Tolimieri–Orr, Bastiaans and Van-Leest and others. In our presentation the spreading representation of linear operators between finite-dimensional Hilbert space as well as a symplectic version of Poisson's summation formula over the finite time–frequency plane are essential ingredients. They bring us to the so-called Fundamental Identity of Gabor Analysis. In addition, we highlight projective representations of the time–frequency plane and its subgroups and explain the natural connection to twisted group algebras. In the finite-dimensional setting discussed in this paper these twisted group algebras are just matrix algebras and their structure provides the algebraic framework for the study of the deeper properties of finite-dimensional Gabor frames, independent of the structure theory theorem for finite Abelian groups.     

Re-designing industrial products on a multi-objective basis: a case study

Environmentally conscious product design has received significant attention recently. Apart from new products’ development, environmental considerations may also apply for products that manufacturers have already launched in the market. In this case, manufacturers can also make use of their considerable experience gained over the phases following product design (eg production, use, end-of-life, etc) in order to promote substantial improvements as regards their re-designed products’ performance. This paper presents a methodological framework for manufacturers based on Multiple Objective Integer Programming in order to re-design industrial products. The proposed approach includes re-designed product's cost, environmental impact, weight and ease of disassembly. The methodology is applied to a real-world case study, that of netMod network terminal.     

Denumerable controlled Markov chains with strong average optimality criterion: Bounded & unbounded costs

This paper studies discrete-time nonlinear controlled stochastic systems, modeled by controlled Markov chains (CMC) with denumerable state space and compact action space, and with an infinite planning horizon. Recently, there has been a renewed interest in CMC with a long-run, expected average cost (AC) optimality criterion. A classical approach to study average optimality consists in formulating the AC case as a limit of the discounted cost (DC) case, as the discount factor increases to 1, i.e., as the discounting effectvanishes. This approach has been rekindled in recent years, with the introduction by Sennott and others of conditions under which AC optimal stationary policies are shown to exist. However, AC optimality is a rather underselective criterion, which completely neglects the finite-time evolution of the controlled process. Our main interest in this paper is to study the relation between the notions of AC optimality andstrong average cost (SAC) optimality. The latter criterion is introduced to asses the performance of a policy over long but finite horizons, as well as in the long-run average sense. We show that for bounded one-stage cost functions, Sennott's conditions are sufficient to guarantee thatevery AC optimal policy is also SAC optimal. On the other hand, a detailed counterexample is given that shows that the latter result does not extend to the case of unbounded cost functions. In this counterexample, Sennott's conditions are verified and a policy is exhibited that is both average and Blackwell optimal and satisfies the average cost inequality.     

A utility measure for finding multiobjective shortest paths in urban multimodal transportation networks

In this paper we study the problem of finding Origin–Destination (O–D) shortest paths in urban multimodal transportation networks, aiming at minimizing the overall cost, time and users' discommodity associated with the required paths. We present an approach based on the classical shortest path problem on a network representing the urban multimodal transportation system, i.e. the private, the public and the pedestrian modalities. Our idea is to make use of an ad hoc utility function for weighing the arcs both with their cost and time and considering at the same time the preference of the users related to all the possible transportation modalities. In particular, a utility measure is presented taking into a proper account the different users' propensities. The proposed approach has been developed for analysing the urban transportation network of an Italian city; the first experimental results are given in the paper.     

Modeling framework for membrane computing in biological systems: Evaluation with a case study

Membrane computing can represent the structures and behaviors of biological systems while considering their characteristics. This paper proposes a modeling framework for membrane computing in biological systems to provide guidelines when using and experimenting with membrane computing. The framework processes include the biological requirements and property specifications, membrane computing model, membrane computing simulation strategy, and model checking approach. A biological system that comprised the ligand–receptor networks of TGF-β protein was used as a case study to evaluate the framework. The evaluation of the framework demonstrated that membrane computing performed better than conventional ordinary differential equations when capturing the structure and behavior of biological systems.     

On electromagnetic waves in complex linear media in nonsmooth domains

Electromagnetic wave propagation in more complex linear materials such as bi‐anisotropic media have come to a considerable attention within the last 15–20 years. We shall propose a general framework to approach a class of highly complex materials. Such problems have been extensively studied mostly in the time‐harmonic case. In this paper, we focus on the time‐dependent case. A well‐posedness result for a large class of media is obtained. We also analyze Drude–Born–Fedorov type media in nonsmooth domains of arbitrary topological genus within this framework. Copyright © 2012 John Wiley & Sons, Ltd.     

Risk and quality control in a supply chain: competitive and collaborative approaches

This paper provides a quantitative and comparative economic and risk approach to strategic quality control in a supply chain, consisting of one supplier and one producer, using a random payoff game. Such a game is first solved in a risk-neutral framework by assuming that both parties are competing with each other. We show in this case that there may be an interior solution to the inspection game. A similar analysis under a collaborative framework is shown to be trivial and not practical, with a solution to the inspection game being an ‘all or nothing’ solution to one or both the parties involved. For these reasons, the sampling random payoff game is transformed into a Neyman–Pearson risk constraints game, where the parties minimize the expected costs subject to a set of Neyman–Pearson risk (type I and type II) constraints. In this case, the number of potential equilibria can be large. A number of such solutions are developed and a practical (convex) approach is suggested by providing an interior (partial sampling) solution for the collaborative case. Numerical examples are developed to demonstrate the procedure used. Thus, unlike theoretical approaches to the solution of strategic quality control random payoff games, the approach we construct is both practical and consistent with the statistical risk Neyman–Pearson approach.     

Exact integration of the stiffness matrix of an 8‐node plane elastic finite element by symbolic computation

Computer algebra systems (CAS) are powerful tools for obtaining analytical expressions for many engineering applications in both academic and industrial environments. CAS have been used in this paper to generate exact expressions for the stiffness matrix of an 8‐node plane elastic finite element. The Maple software system was used to identify six basic formulas from which all the terms of the stiffness matrix could be obtained. The formulas are functions of the Cartesian coordinates of the corner nodes of the element, and elastic parameters Young's modulus and Poisson's ratio. Many algebraic manipulations were performed on the formulas to optimize their efficiency. The redaction in CPU time using the exact expressions as opposed to the classical Gauss–Legendre numerical integration approach was over 50%. In an additional study of accuracy, it was shown that the numerical approach could lead to quite significant errors as compared with the exact approach, especially as element distortion was increased.© 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 2007     

Operational and economic efficiency analysis of public hospitals in Greece

The continuous growth of hospital costs has driven governments in many countries to seek ways to improve their efficiency. In Greece, this has consistently been a major issue for almost two decades, as efficiency assessment and monitoring systems are lacking. In response to this need, the evaluation of the National Health System hospitals’ efficiency level is a precondition for planning, implementing and monitoring any promising reform. In this paper, a non-parametric modeling approach is employed to assess and analyze the efficiency of 87 Greek public hospitals over the period 2005–2009, using data envelopment analysis. The operational and economic aspects of the hospitals’ operation are considered on the basis of their service/case mix and cost structure. We also investigate the efficiency trends over time with the Malmquist index and a second stage regression analysis is performed to explain the operational and economic efficiency results in terms of the hospitals’ operating characteristics and the environment in which they operate.     

The effect of different arrival rates on the N-policy of M/G/1 with server setup

It is very important in many real-life systems to decide when the server should start his service because frequent setups inevitably make the operating cost too high. Furthermore, today's systems are too intelligent for the input to be assumed as a simple homogenous Poisson process. In this paper, an M/G/1 queue with general server setup time under a control policy is studied. We consider the case when the arrival rate varies according to the server's status: idle, setup and busy states. We derive the distribution function of the steady-state queue length, as well as the Laplace–Stieltjes transform of waiting time. For this model, the optimal N-value from which the server starts his setup is found by minimizing the total operation cost of the system. We finally investigate the behavior of system operation cost and the optimal N for various arrival rates by a numerical study.     

A calibrated model of local food system of Hawaii: What are the economic implications of the state's food goals and policies?

We develop a fully calibrated positive mathematical programming model for Hawaii's local food systems—which captures the production and the consumer sides of the market. Then we use the model to assess two proposed policies—a general excise tax (GET) exemption on locally produced foods, and an investment in agricultural infrastructure. For the GET exemption case, our results indicate an economic gain of $118 per $100 cost. On the other hand, an investment in 1,200 acres of land injected to support local production may generate an economic gain of up to $357 per $100 annual cost of the investment. However, these estimates should be considered preliminary, and thus viewed with caution. Although the model is used to capture Hawaii's local food systems, we believe that our model is generalizable and can be adopted by other economies to assess their respective food localization policies. Recommendations for Resource Managers

• Local food policies need to be based on quantitative terms instead of mere armchair speculation because often their potential outcomes may vary significantly.

• The current modeling framework demonstrates the potential of using positive mathematical programming (PMP) in capturing the intricacies of local food systems. However, this exploratory exercise should be viewed as preliminary in nature and the ensuing results were taken with caution because many important factors such as labor availability may have been left out.

• Thus, further model refinements are necessary to better capture the complexities of local food systems such as farm heterogeneity, availability of farm labor, water availability, and interisland transportation of farm products in the case of Hawaii.

     

Problem structuring in project management: an application of soft systems methodology (SSM)

Recent research suggests a major role for problem structuring methods (PSMs) in the field of project management, particularly at the front-end of projects, where objectives are often unclear and where different constituencies have conflicting aims. This paper presents a case example of soft systems methodology (SSM) at the front-end of a major project within Tesco Stores Ltd. A detailed account of the intervention is given, including the results achieved and a discussion of how the methodology was used for multiple purposes within the same intervention. Within the literature, there remains a lack of detailed examples from which people can learn more about the use of PSMs in project management. By providing a detailed example of SSM in action, this paper seeks to highlight the importance of problem structuring at the front-end of projects and the potential role an approach such as SSM can play at this crucial stage.     

Characterizing an equitable allocation of shared costs: A DEA approach

In many applications to which DEA could be applied, there is often a fixed or common cost which is imposed on all decision making units. This would be the case, for example, for branches of a bank which can be accessed via the numerous automatic teller machines scattered throughout the country. A problem arises as to how this cost can be assigned in an equitable way to the various DMUs. In this paper we propose a DEA approach to obtain this cost allocation which is based on two principles: invariance and pareto-minimality. It is shown that the proposed method is a natural extension of the simple one-dimensional problem to the general multiple-input multiple-output case.     

Index policies for the maintenance of a collection of machines by a set of repairmen

A collection of M machines which deteriorate under usage is maintained by a set of R repairmen who may have other tasks to perform. Maintenance interventions will improve a machine's condition and may preempt costly breakdowns. The problem of scheduling such interventions to minimise the total expected discounted cost incurred in operating the machines over an infinite horizon is formulated as a Markov Decision Process which has the form of a restless bandit problem. We outline an approach to the development of maintenance policies based on simple machine indices in the form of a fair charge for a maintenance intervention in the machine's current state. Closed form indices are derived for two particular models. Numerical investigations demonstrate the strong performance of the derived index heuristics.     

Mixing methodologies for information systems development and strategy: A higher education case study

Although informed approaches from an interpretivist perspective have been widely promoted over the last two decades information systems development is largely informed by a functionalist perspective, into which human-centred or interpretivist issues are incorporated as they are seen to be required. By treating such developments as critically informed social systems, this paper offers an alternative viewpoint. Firstly, a theoretical justification for such an approach is offered, drawing on developments in Critical Management Science, themselves based on a strand of Critical Social Theory. Secondly, an action research-based intervention is detailed, demonstrating the practical applicability of such an approach, an applicability that has hitherto been questioned. The outcome is a synthesised approach to operational and strategic information systems development, within a critical framework, which, it is argued, offers a greater potential for success than the currently promoted approaches.     

Fifty years of systems thinking for management

The point of this paper is to provide an account of the last 50 years of systems thinking applied to management that is insightful and useful to those interested in the theory and practice of operational research (OR). In seeking to fulfil this purpose, it employs Boulding's well-known ‘hierarchy of complexity’ to think through the reasons for the emergence of different strands of applied systems thinking and to detail their strengths. In theoretical terms, operational researchers will find a number of the key issues that have engaged their field (eg, hard versus soft approaches) mirrored in debates that have taken place between systems thinkers. They may discover new theoretical avenues to follow to advance their discipline. OR practitioners may also be surprised by the nature and scope of the systems applications described and conclude that systems approaches should be added to their own intervention strategies. At the least, the paper is designed to reinvigorate discussion around the relationship between OR and systems thinking that has occasionally surfaced over the last half century but has never been satisfactorily concluded.     

Exact formulation of stochastic EMQ model for an unreliable production system

The purpose of this paper is to present an exact formulation of stochastic EMQ model for an unreliable production system under a general framework in which the time to machine failure, corrective (emergency) and preventive (regular) repair times are assumed to be random variables. For exact financial implications of the lot-sizing decisions, the EMQ model is formulated based on the net present value (NPV) approach. Then, by taking limitation on the discount rate, the traditional long-run average cost model is obtained. The criteria for the existence and uniqueness of the optimal production time in both the models are derived under general failure and specific repair time distributions. Numerical examples are devoted to find the optimal production policies of the developed models and examine the sensitivity of the parameters involved. Computational results show that the optimal decision based on the NPV approach is superior to that based on the long-run average cost approach, though the performance level strongly depends on the pertinent failure and repair time distributions.     

A hybrid model based on dynamic programming,neural networks,and surrogate value for inventory optimisation applications

This paper proposes a new approach to minimise inventory levels and their associated costs within large geographically dispersed organisations. For such organisations, attaining a high degree of agility is becoming increasingly important. Linear regression-based tools have traditionally been employed to assist human experts in inventory optimisation; endeavours; recently, Neural Network (NN) techniques have been proposed for this domain. The objective of this paper is to create a hybrid framework that can be utilised for analysis, modelling and forecasting purposes. This framework combines two existing approaches and introduces a new associated cost parameter that serves as a surrogate for customer satisfaction. The use of this hybrid framework is described using a running example related to a large geographically dispersed organisation.     

Effective cancellation policy to reduce the negative impact of patient no-show

The problem of patient no-show in outpatient delivery systems has been a long recognized issue. The negative impacts include underutilized medical resources, increased healthcare costs, decreased access to care, and reduced clinic efficiency and provider productivity. Many clinics have cancellation policies of asking their patients to cancel 24 or 48?h in advance. However, there is no logical or mathematical basis for such a policy. The objective is to develop an effective cancellation policy that accounts for current no-show rates, the clinic's flow, and its fill rates to minimize the cost of patient wait time, physician idle time, and overtime. A simulation approach is presented to determine the hours required for patients to call in advance for cancelling appointments. The findings indicate that when fill rates are low and no-show probabilities are high, the time required for patients to cancel appointments needs to increase in order to achieve the goal of being cost-effective.     

A short proof of convexity of step-out–step-in sequencing games

The Step out–Step in sequencing game is a particular example of a game from the sequencing game framework of Curiel, Perderzoli, and Tijs, where coalitions of players in a queue may reorder themselves to improve the their overall cost, under some restrictions. Musegaas, Borm and Quant proved, in two papers, that a simple greedy algorithm correctly computes the valuation of a coalition, and that the game is convex. These proofs entail rather involved case analyses; in this note, we give short proofs of both results.