The “problem” in and of management information systems

Management Information Systems uncritically draws upon a number of disciplines for its theoretical framework. In doing so it has imported a host of ontological, epistemological and behavioral assumptions which have shaped the theories, technologies and practices of information system analysis, design and implementation. This has taken place without careful reflection upon the historical emergence of these assumptions or upon the context within which attempts are made to operationalize them. This paper argues that the Management Information Systems field is in need of researching itself. It proposes that through a combination of genealogical and ethnographic research methodologies, the historical emergence of theoretical constructs and the organizational context within which information systems operate should be critically examined. In the following analysis, the historical emergence of the “problem” as a generic construct in the Management Information System literature is examined and contrasted to the manner in which a group of manufacturing managers defined problems within their organizational context. A critical tension is revealed which suggests that information systems researchers, analysts and designers need to at least broaden their assumption about the nature of organizational reality, human behavior, information processing and problem solving.     

Projection type neural network and its convergence analysis

Projection type neural network for optimization problems has advantages over other networks for fewer parameters , low searching space dimension and simple structure. In this paper, by properly constructing a Lyapunov energy function, we have proven the global convergence of this network when being used to optimize a continuously differentiable convex function defined on a closed convex set. The result settles the extensive applicability of the network. Several numerical examples are given to verify the efficiency of the network.     

Discrete-time delayed standard neural network model and its application

The research on the theory and application of artificial neural networks has achieved a great success over the past two decades. Recently, increasing attention has been paid to recurrent neural networks, which are rich in dynamics, highly parallelizable, and easily implementable with VLSI. Due to these attractive features, RNNs have widely been applied to system identification, control, optimization and associative memories[1]. Stability analysis, which is critical to any applications of R…     

A novel fuzzy neural network and its approximation capability

The polygonal fuzzy numbers are employed to define a new fuzzy arithmetic. A novel ex-tension principle is also introduced for the increasing function σ:R→R. Thus it is convenient to con-struct a fuzzy neural network model with succinct learning algorithms. Such a system possesses some universal approximation capabilities, that is, the corresponding three layer feedforward fuzzy neural networks can be universal approximators to the continuously increasing fuzzy functions.     

The Deutsch–Jozsa problem: de-quantisation and entanglement

The Deutsch–Jozsa problem is one of the most basic ways to demonstrate the power of quantum computation. Consider a Boolean function f : {0, 1} ⁿ → {0, 1} and suppose we have a black-box to compute f. The Deutsch–Jozsa problem is to determine if f is constant (i.e. f(x) = const, "x ? {0,1}ⁿf(x) = \hbox {const, } \forall x \in \{0,1\}^n) or if f is balanced (i.e. f(x) = 0 for exactly half the possible input strings x ? {0,1}ⁿx \in \{0,1\}^n) using as few calls to the black-box computing f as is possible, assuming f is guaranteed to be constant or balanced. Classically it appears that this requires at least 2 ⁿ⁻¹ + 1 black-box calls in the worst case, but the well known quantum solution solves the problem with probability one in exactly one black-box call. It has been found that in some cases the algorithm can be de-quantised into an equivalent classical, deterministic solution. We explore the ability to extend this de-quantisation to further cases, and examine with more detail when de-quantisation is possible, both with respect to the Deutsch–Jozsa problem, as well as in more general cases.     

Semi-tensor product of matrices and its application to Morgen’s problem

This paper proposes a new matrix product, namely, semi-tensor product. It is a generalization of the conventional matrix product. Meanwhile, it is also closely related to Kronecker (tensor) product of matrices. The purpose of introducing this product is twofold: (i) treat multi-dimensional data; (ii) treat nonlinear problems in a linear way. Then the computer and numerical methods can be easily used for solving nonlinear problems. Properties and formulas are deduced. As an application, the Morgen’s problem for control systems is formulated as a numerically solvable problem.     

Ordinal scheduling problem and its asymptotically optimal algorithms on parallel machine system

Consider a resource allocation problem on the following system. A system consists of m identical parallel machines and is alive only when all the machines are alive. To keep a machine alive, it requires resources (material, fuel, etc.). Resources with various sizes arrive one by one and the goal is to keep the system alive as long as possible. The problem has applications in many areas such as sequencing of maintenance actions for modular gas turbine aircraft engines[1]. Using scheduling term…     

A university-timetabling problem and its solution using Benders’ partitioning—a case study

In this paper, we address a university-timetabling problem and present a methodology that relies on Benders’ partitioning for its solution. This partitioning results from the special nature of the underlying integer programming formulation for this problem. We have used our methodology to schedule courses offered by the College of Engineering as well as to those offered university-wide at Virginia Tech. The results clearly depict an improvement in the quality of course schedules obtained by our methodology over those currently used, when the performance of a timetable is measured by the total distance traveled by the faculty members from their offices in respective departments to the classrooms, where the courses are offered.     

The ‘Japan problem’ in science and technology and basic research as a culture

This paper analyses the Japan Problem in science and technology from the viewpoint of the cultural factors involved. The selective use of contrary images of society depending on social context gives rise to a self-amplification of the problem. The paper critically examines what such generating mechanisms imply for a linear model connecting scientific, technological and economic performances. By focusing on the Science and Technology Basic Law and Plan approved in Japan in 1995 and 1996, it argues that measures taken for the promotion of basic research and creativity without giving due consideration to the relevant cultural factors provide an unsound basis for evaluating basic research. The paper argues that self-organisation by self-reference could provide an important general principle for human-centred science and technology policy, and especially policy for basic research.With Senior Associate Membership of St Antony's College, University of Oxford, UK for 1998–1999     

A modified fuzzy min–max neural network with rule extraction and its application to fault detection and classification

The fuzzy min–max (FMM) network is a supervised neural network classifier that forms hyperboxes for classification and prediction. In this paper, we propose modifications to FMM in an attempt to improve its classification performance when a small number of large hyperboxes are formed in the network. Given a new input pattern, in addition to measuring the fuzzy membership function of the input pattern to the hyperboxes formed in FMM, an Euclidean distance measure is introduced for predicting the target class associated with the new input pattern. A rule extraction algorithm is also embedded into the modified FMM network. A confidence factor is calculated for each FMM hyperbox, and a user-defined threshold is used to prune the hyperboxes with low confidence factors. Fuzzy if–then rules are then extracted from the pruned network. The benefits of the proposed modifications are twofold, viz., to improve the performance of FMM when large hyperboxes are formed in the network; to facilitate the extraction of a compact rule set from FMM to justify its predictions. To assess the effectiveness of modified FMM, two benchmark pattern classification problems are experimented, and the results from different methods published in the literature are compared. In addition, a fault detection and classification problem with a set of real sensor measurements collected from a power generation plant is evaluated using modified FMM. The results obtained are analyzed and explained, and implications of the modified FMM network as a useful fault detection and classification tool in real environments are discussed.     

Special issue on “Soft computing techniques: applications and challenges” neural computing and applications

Neural Computing and Applications -     

The symbol grounding problem … remains unsolved

Taddeo and Floridi [2007. A praxical solution of the symbol grounding problem. Minds and Machines, 17, 369–389. (This paper is reprinted in Floridi, L. (2011). The philosophy of information. Oxford: Oxford University Press)] propose a solution to the symbol grounding problem (SGP). Unfortunately, their proposal, while certainly innovative, interesting and – given the acute difficulty of SGP – brave, merely shows that a class of robots can in theory connect, in some sense, the symbols it manipulates with the external world it perceives, and can, on the strength of that connection, communicate in sub-human fashion.     

Hamilton–Jacobi–Bellman Quasi-Variational Inequality arising in an environmental problem and its numerical discretization

A Hamilton–Jacobi–Bellman Quasi-Variational Inequality (HJBQVI) for a river environmental restoration problem with wise-use of sediment is formulated and its mathematical properties are analyzed. A finite difference scheme with a penalization technique is then established for solving the HJBQVI. The scheme is free from any iterative solvers and is unconditionally stable and convergent in the viscosity sense under certain conditions. A demonstrative application example of the HJBQVI is finally presented.     

A cost-optimal parallel algorithm for the 0–1 knapsack problem and its performance on multicore CPU and GPU implementations

The 0–1 knapsack problem has been extensively studied in the past years due to its immediate applications in industry and financial management, such as cargo loading, stock cutting, and budget control. Many algorithms have been proposed to solve this problem, most of which are heuristic, as the problem is well-known to be NP-hard. Only a few optimal algorithms have been designed to solve this problem but with high time complexity. This paper proposes the cost-optimal parallel algorithm (COPA) on an EREW PRAM model with shared memory to solve this problem. COPA is scalable and yields optimal solutions consuming less computational time. Furthermore, this paper implements COPA on two scenarios – multicore CPU based architectures using Open MP and GPU based configurations using CUDA. A series of experiments are conducted to examine the performance of COPA under two different test platforms. The experimental results show that COPA could reduce a significant amount of execution time. Our approach achieves the speedups of up to 10.26 on multicore CPU implementations and 17.53 on GPU implementations when the sequential dynamic programming algorithm for KP01 is considered as a baseline. Importantly, GPU implementations outstand themselves in the experimental results.     

Multi-objective mitigation budget allocation problem and solution approaches: The case of İstanbul

İstanbul is the financial, commercial, industrial, cultural and educational center of Turkey. However, İstanbul is also an earthquake-prone city that has experienced many earthquakes throughout its history; and it is threatened with a high probability of a devastating earthquake in the next 30 years. In this study, we propose three financial allocation strategies and their multi-objective models related to building reinforcement, with the purpose of reducing the risk of disaster in Istanbul. The study aims to answer three important questions: (1) How should the mitigation budget be distributed among Istanbul’s districts? (2) Which building types should be mitigated, and how? (3) Can Pareto-efficient solutions be sorted? Pareto-efficient solutions for all of the proposed models were obtained and analyzed. The proposed superefficiency model has the ability to rank the Pareto-optimal solutions.     

The train driver recovery problem—A set partitioning based model and solution method

The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Based on data from the Danish passenger railway operator DSB S-tog A/S, a solution method to the train driver recovery problem (TDRP) is developed. The TDRP is formulated as a set partitioning problem. We define a disruption neighbourhood by identifying a small set of drivers and train tasks directly affected by the disruption. Based on the disruption neighbourhood, the TDRP model is formed and solved. If the TDRP solution provides a feasible recovery for the drivers within the disruption neighbourhood, we consider that the problem is solved. However, if a feasible solution is not found, the disruption neighbourhood is expanded by adding further drivers or increasing the recovery time period. Fractional solutions to the LP relaxation of the TDRP are resolved with a constraint branching strategy using the depth-first search of the Branch & Bound tree. The LP relaxation of the TDRP possesses strong integer properties. We present test scenarios generated from the historical real-life operations data of DSB S-tog A/S. The numerical results show that all but one tested instances produce integer solutions to the LP relaxation of the TDRP and solutions are found within a few seconds.