Choice of the organization structure: A framework for quantitative analysis of industrial centralization/decentralization issues

Quantitative analysis of centralization/decentralization problems has so far mainly centered around the question of how decentralization might be achieved without departing from the system optimum, involving decomposition techniques of linear and nonlinear models. Positive effects, besides division of labour, of an application of the decentralization principle to a firm's organization were not taken into account. In order to do so, a decision model for a hypothetical industrial organization has been developed, leading to a comparison of the effectiveness of various more or less decentralized organization structures. The problem appears to be one in capital budgeting, where management is required to generate information of sub-unit performance through a heuristic routine. System alternatives may be ranked by one or more evaluation criteria, the one with highest rank, compared to present achievement, indicating steps toward desirable organizational change of the system. For simplicity's sake, the model, in a first stage, has been conceived as static and deterministic. A numerical example is given.

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Zusammenfassung Die quantitative Analyse von Zentralisierungs- und Dezentralisierungsproblemen konzentrierte sich bisher auf die Frage, wie Dezentralisierung ohne Verletzung des Systemoptimums unter Zentralisierung erreicht werden konnte, wozu die Dekompositionstechniken für lineare und nicht lineare Modelle herangezogen werden. Positive Effekte der Anwendung des Dezentralisationsprinzips auf die Unternehmensorganisation neben der Arbeitsteilung wurden außer Betracht gelassen. Um diese positiven Effekte berücksichtigen zu können, wurde ein Entscheidungsmodell für eine hypothetische Unternehmensorganisation entwickelt, welches zu einem Vergleich der Effizienz verschiedener mehr oder weniger dezentralisierter Organisationsstrukturen führt. Man erhält ein Problem der Kapitalbewirtschaftung, wobei die Unternehmensleitung Informationen über die Effizienz von in der Hierarchie nachgelagerten Instanzen mit Hilfe heuristischer Verfahren erzeugen muß. Die Systemalternativen können dann nach einem oder mehreren Auswahlkriterien in eine Rangstufung gebracht werden, wobei diejenige Alternative gewählt wird, welche im Vergleich zum Istzustand den höchsten Rang einnimmt. Zur Vereinfachung wurde das Modell statisch und deterministisch konzipirt. Ein Beispiel dient der Erläuterung.

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Revised version of a paper given at the Twentieth International Meeting of the Institute of Management Science, Tel Aviv June 1973.     

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.     

A study on the persistence of Farrell’s efficiency measure under a dynamic framework

This article introduces a sequence of four systematic methods to examine the extent to which the economic efficiency of Taiwan’s commercial banks persists and to uncover the potential dynamic link between bank performance and various financial indicators. Quasi-fixed inputs are explicitly incorporated in the DEA model to account for possible adjustment costs, regulation, or indivisibilities. Among the four methods, the dynamic panel data model and the Markov model appear to be exploited for the first time in the area of the DEA approach. Evidence is found that bank efficiency exhibits moderate persistence over the sample period, implying that the given sample banks fail to adjust their production techniques in a timely manner. Regulatory authorities and bank managers are suggested to be aware of the level of undesirable non-performing loans due to their close relationship with bank performance.     

A quantitative study on the stability of delay discrete singular systems

For quadratic delay discrete singular systems, an algebraic criterion on the stability is established, and the size of the uniform stability region and asymptotic stability region around zero is estimated. Hence, the criterion is both qualitative and quantitative. With the computer techniques, the criterion dependent of delay is easy test and applies to the application in the practice. An illustrative simulation is given to illustrate the application of the obtained result.     

Some notes on the spectral perturbations of the signless Laplacian of a graph

Let G be a simple graph and let Q（G） be the signless Laplacian matrix of G. In this paper we obtain some results on the spectral perturbation of the matrix Q（G） under an edge addition or an edge contraction.     

A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO

This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has been proposed so far, and an attempt of conceptually unifying existing approaches is presented here. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. This model is then incorporated into the ParadisEO-MOEO software framework. This framework has proven its validity and high flexibility by enabling the resolution of many academic, real-world and hard multiobjective optimization problems.     

A probabilistic framework for the continuous observation of a quantum process

This paper treats quantum measurement within von Neumann's abstract framework. Specifically, observation is defined as a fixed self-adjoint operator with countable spectrum and nondegenerate eigenstates. Suppose scenarios for the observation of a quantum process over time are expanded by adding extra observations at time points interspersed among those of a previous scenario. If each observation leads to a mixture of eigenstates rather than a pure state, then the naturally defined joint probability measures on observed results are not consistent as scenarios vary. Nevertheless, we characterize the limiting subprobability measure when the times of observation become infinitely dense in any finite interval. This limiting measure corresponds to a continuous-time sub-stochastic process which decays with exponential rate out of any initial state and never reappears in any other state. Thus the process loses probability exponentially over time, and this loss occurs equally fast in the case of nonselective observation as for selective observation.Previous treatments of this problem have concentrated on the special case when Zeno's Paradox is in force, i.e. the rate of decay out of any state is zero and the process is immobilized by continuous observation. This situation exists, for instance, when the initial state is in the domain of the generator for the unitary group underlying the quantum process.     

A system-theoretic framework for a wide class of systems II: Input-to-output stability

In this work characterizations of the notion of Weighted Input-to-Output Stability (WIOS) for a wide class of systems with disturbances are given. Particularly, for systems with continuous dependence of the solution on the initial state and the input, the WIOS property is shown to be equivalent to robust forward completeness from the input and robust global asymptotic output stability for the corresponding input-free system.     

A multilevel network study of the effects of delinquent behavior on friendship evolution

A multilevel approach is proposed to the study of the evolution of multiple networks. In this approach, the basic evolution process is assumed to be the same, while parameter values may differ between different networks. For the network evolution process, stochastic actor-oriented models are used, of which the parameters are estimated by Markov chain Monte Carlo methods. This is applied to the study of effects of delinquent behavior on friendship formation, a question of long standing in criminology. The evolution of friendship is studied empirically in 19 school classes. It is concluded that there is evidence for an effect of similarity in delinquent behavior on friendship evolution. Similarity of the degree of delinquent behavior has a positive effect on tie formation but also on tie dissolution. The last result seems to contradict current criminological theories, and deserves further study.     

Capacity augmentation of a supply chain for a short lifecycle product: A system dynamics framework

For an innovative product characterized by short product lifecycle and high demand uncertainty, investment in capacity buildup has to be done cautiously. Otherwise either the product’s market diffusion is impeded or the manufacturer is left with unutilized capacity. Using the right information for making capacity augmentation decisions is critical in facing this challenge. In this paper, we propose a method for identifying critical information flows using the system dynamics model of a two-echelon supply chain. The fundamental premise of system dynamics methodology is that (system) structure determines (its) behavior. Using loop dominance analysis method we study the feedback loop structure of the supply chain system. The outcome is a set of dominant loops that determine the dynamics of capacity growth. It is revealed that the delivery delay information has little effect while the loop that connects retail sales with production order affects the dynamics significantly. Modifying this loop yields appropriate capacity augmentation decisions resulting in higher performance. What-if analyses bring out effects of modifying other structural elements. In conclusion, we claim that the information feedback based methodology is general enough to be useful in designing decision support systems for capacity augmentation. The limitations of the model are also discussed and possible extensions identified.     

Toward the Determination of the Minimum Distance of Two-Point Codes on a Hermitian Curve

This is a first step toward the determination of the parameters of two-point codes on a Hermitian curve. We describe the dimension of such codes and determine the minimum distance of some two-point codes.AMS Classification: 94B27, 14H50, 11T71, 11G20Masaaki Homma - Partially supported by Grant-in-Aid for Scientific Research (15500017), JSPS.Seon Jeong Kim - Partially supported by Korea Research Foundation Grant (KRF-2002-041-C00010).     

A framework and a mean-field algorithm for the local control of spatial processes

The Markov Decision Process (MDP) framework is a tool for the efficient modelling and solving of sequential decision-making problems under uncertainty. However, it reaches its limits when state and action spaces are large, as can happen for spatially explicit decision problems. Factored MDPs and dedicated solution algorithms have been introduced to deal with large factored state spaces. But the case of large action spaces remains an issue. In this article, we define graph-based Markov Decision Processes (GMDPs), a particular Factored MDP framework which exploits the factorization of the state space and the action space of a decision problem. Both spaces are assumed to have the same dimension. Transition probabilities and rewards are factored according to a single graph structure, where nodes represent pairs of state/decision variables of the problem. The complexity of this representation grows only linearly with the size of the graph, whereas the complexity of exact resolution grows exponentially. We propose an approximate solution algorithm exploiting the structure of a GMDP and whose complexity only grows quadratically with the size of the graph and exponentially with the maximum number of neighbours of any node. This algorithm, referred to as MF-API, belongs to the family of Approximate Policy Iteration (API) algorithms. It relies on a mean-field approximation of the value function of a policy and on a search limited to the suboptimal set of local policies. We compare it, in terms of performance, with two state-of-the-art algorithms for Factored MDPs: SPUDD and Approximate Linear Programming (ALP). Our experiments show that SPUDD is not generally applicable to solving GMDPs, due to the size of the action space we want to tackle. On the other hand, ALP can be adapted to solve GMDPs. We show that ALP is faster than MF-API and provides solutions of similar quality for most problems. However, for some problems MF-API provides significantly better policies, and in all cases provides a better approximation of the value function of approximate policies. These promising results show that the GMDP model offers a convenient framework for modelling and solving a large range of spatial and structured planning problems, that can arise in many different domains where processes are managed over networks: natural resources, agriculture, computer networks, etc.     

A system-theoretic framework for a wide class of systems I: Applications to numerical analysis

A system-theoretic framework is proposed, which allows the study of hybrid uncertain systems, which do not satisfy the so-called “semigroup property.” Characterizations of the notion of robust global asymptotic output stability (RGAOS) are given. Based on the provided characterizations, the qualitative behavior of hybrid systems obtained by time-discretization of systems of ordinary differential equations with a globally asymptotically stable equilibrium point, is studied.     

Connected functional working spaces: a framework for the teaching and learning of functions at upper secondary level

ZDM – Mathematics Education - This paper aims at contributing to remedy the narrow treatment of functions at upper secondary level. Assuming that students make sense of functions by working...     

Decomposition of conflict as a distribution on hypotheses in the framework on belief functions

In this paper, we address the problem of identifying the potential sources of conflict between information sources in the framework of belief function theory. To this aim, we propose a decomposition of the global measure of conflict as a function defined over the power set of the discernment frame. This decomposition, which associates a part of the conflict to some hypotheses, allows identifying the origin of conflict, which is hence considered as “local” to some hypotheses. This is more informative than usual global measures of conflict or disagreement between sources. Having shown the unicity of this decomposition, we illustrate its use on two examples. The first one is a toy example where the fact that conflict is mainly brought by one hypothesis allows identifying its origin. The second example is a real application, namely robot localization, where we show that focusing the conflict measure on the “favored” hypothesis (the one that would be decided) helps us to robustify the fusion process.     

Math MOOC UniTo : an Italian project on MOOCs for mathematics teacher education,and the development of a new theoretical framework

This paper focuses on MOOCs (massive open online courses), a fairly recent paradigm in e-learning educational projects. Despite the high dropout rate, and     

Identifying critical financial networks of the DJIA: Toward a network‐based index

The purpose of this article is twofold. First, we introduce a novel definition of financial networks obtained from time series data from the stock market. Second, we demonstrate that these networks can be used as an index with the property to reflect critical states of the market, respectively, crashes sufficiently. Our work aims to advocate a network‐based analysis in the context of the stock market, because such a collective phenomenon can not only be economically described by networks but also analyzed as demonstrated in this article. © 2010 Wiley Periodicals, Inc. Complexity 16: 24–33, 2010     

A double projection algorithm for multi-valued variational inequalities and a unified framework of the method

In this paper, we propose a double projection algorithm for a generalized variational inequality with a multi-valued mapping. Under standard conditions, our method is proved to be globally convergent to a solution of the variational inequality problem. Moreover, we present a unified framework of projection-type methods for multi-valued variational inequalities. Preliminary computational experience is also reported.     

A capacity-rounding algorithm for the minimum-cost circulation problem: A dual framework of the Tardos algorithm

Recently, É. Tardos gave a strongly polynomial algorithm for the minimum-cost circulation problem and solved the open problem posed in 1972 by J. Edmonds and R.M. Karp. Her algorithm runs in O(m ² T(m, n) logm) time, wherem is the number of arcs,n is the number of vertices, andT(m, n) is the time required for solving a maximum flow problem in a network withm arcs andn vertices. In the present paper, taking an approach that is a dual of Tardos's, we also give a strongly polynomial algorithm for the minimum-cost circulation problem. Our algorithm runs in O(m ² S(m, n) logm) time and reduces the computational complexity, whereS(m, n) is the time required for solving a shortest path problem with a fixed origin in a network withm arcs,n vertices, and a nonnegative arc length function. The complexity is the same as that of Orlin's algorithm, recently developed by efficiently implementing the Edmonds-Karp scaling algorithm.