A new mixed integer linear programming model for product development using quality function deployment

Quality function deployment (QFD) is a product development process performed to maximize customer satisfaction. In the QFD, the design requirements (DRs) affecting the product performance are primarily identified, and product performance is improved to optimize customer needs (CNs). For product development, determining the fulfillment levels of design requirements (DRs) is crucial during QFD optimization. However, in real world applications, the values of DRs are often discrete instead of continuous. To the best of our knowledge, there is no mixed integer linear programming (MILP) model in which the discrete DRs values are considered. Therefore, in this paper, a new QFD optimization approach combining MILP model and Kano model is suggested to acquire the optimized solution from a limited number of alternative DRs, the values of which can be discrete. The proposed model can be used not only to optimize the product development but also in other applications of QFD such as quality management, planning, design, engineering and decision-making, on the condition that DR values are discrete. Additionally, the problem of lack of solutions in integer and linear programming in the QFD optimization is overcome. Finally, the model is illustrated through an example.     

Investigating the usability of real-time scheduling theory with the Cheddar project

This article deals with real-time critical systems modelling and verification. Real-time scheduling theory provides algebraic methods and algorithms in order to make timing constraints verifications of these systems. Nevertheless, many industrial projects do not perform analysis with real-time scheduling theory even if demand for use of this theory is large and the industrial application field is wide (avionics, aerospace, automotive, autonomous systems, …). The Cheddar project investigates why real-time scheduling theory is not used and how its usability can be increased. The project was launched at the University of Brest in 2002. In Lecture Notes on Computer Sciences, vol. 5026, pp. 240–253, 2008, we have presented a short overview of this project. This article is an extended presentation of the Cheddar project, its contributions and also its ongoing works.     

Data mining-based materialized view and index selection in data warehouses

Materialized views and indexes are physical structures for accelerating data access that are casually used in data warehouses. However, these data structures generate some maintenance overhead. They also share the same storage space. Most existing studies about materialized view and index selection consider these structures separately. In this paper, we adopt the opposite stance and couple materialized view and index selection to take view–index interactions into account and achieve efficient storage space sharing. Candidate materialized views and indexes are selected through a data mining process. We also exploit cost models that evaluate the respective benefit of indexing and view materialization, and help select a relevant configuration of indexes and materialized views among the candidates. Experimental results show that our strategy performs better than an independent selection of materialized views and indexes.     

Betriebsinformatik und Wirtschaftsinformatik als notwendige anwendungsbezogene Ergänzung einer allgemeinen Informatik – Vorschläge zur Verbesserung der akademischen Ausbildung auf dem Gebiet der automatisierten Datenverarbeitung in der Bundesrepublik Deutschland

Zusammenfassung  Nachdruck eines Aufsatzes aus elektronische datenverarbeitung 11(11)1969:544–548. This article is also available in English via and : Grochla E (2008) Corporate Information Systems Engineering and Business and Information Systems Engineering as a Necessary Application-Oriented Extension of General Computer Science – Proposals for Enhancing Academic Education in the Field of Automated Data Processing in the Federal Republic of Germany. Bus Inf Syst Eng. doi .

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Integrated control design for driver assistance systems based on LPV methods

The paper proposes a control design method for a driver assistance system. In the operation of the system, a predefined trajectory required by the driver with a steering command is followed. During manoeuvres the control system generates differential brake moment and the auxiliary front-wheel steering angle and changes the camber angles of the wheels in order to improve the tracking of the road trajectory. The performance specifications are guaranteed by the local controllers, i.e. the brake, the steering, and the suspension systems, while the coordination of these components is provided by the supervisor. The advantage of this architecture is that local controllers are designed independently, which is ensured by the fact that the monitoring signals are taken into consideration in the formalisation of their performance specifications. The fault-tolerant control can be achieved by incorporating the detected fault signals in their performance specifications. The control system also uses a driver model, with which the reference signal can be generated. In the control design, the parameter-dependent linear parameter-varyingmethod, which meets the performance specifications, is used. The operation of the control system is illustrated through different normal and emergency vehicle manoeuvres with a high-accuracy simulation software.     

Inner approximations of completely positive reformulations of mixed binary quadratic programs: a unified analysis

Every quadratic programming problem with a mix of continuous and binary variables can be equivalently reformulated as a completely positive optimization problem, that is, a linear optimization problem over the convex but computationally intractable cone of completely positive matrices. In this paper, we focus on general inner approximations of the cone of completely positive matrices on instances of completely positive optimization problems that arise from the reformulation of mixed binary quadratic programming problems. We provide a characterization of the feasibility of such an inner approximation as well as the optimal value of a feasible inner approximation. In particular, our results imply that polyhedral inner approximations are equivalent to a finite discretization of the feasible region of the original completely positive optimization problem. Our characterization yields, as a byproduct, an upper bound on the gap between the optimal value of an inner approximation and that of the original instance. We discuss the implications of this error bound for standard and box-constrained quadratic programs as well as general mixed binary quadratic programs with a bounded feasible region.     

Mobile multi-view object image search

High user interaction capability of mobile devices can help improve the accuracy of mobile visual search systems. At query time, it is possible to capture multiple views of an object from different viewing angles and at different scales with the mobile device camera to obtain richer information about the object compared to a single view and hence return more accurate results. Motivated by this, we propose a new multi-view visual query model on multi-view object image databases for mobile visual search. Multi-view images of objects acquired by the mobile clients are processed and local features are sent to a server, which combines the query image representations with early/late fusion methods and returns the query results. We performed a comprehensive analysis of early and late fusion approaches using various similarity functions, on an existing single view and a new multi-view object image database. The experimental results show that multi-view search provides significantly better retrieval accuracy compared to traditional single view search.