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SCIENTIFIC & TECHNICAL PROGRAM Monday 09:00-10:30 Hotel Juan Carlos I Plenari Venue: Salón Maremagnum Domingo Pérez-Alonso (IBERDROLA) : Integration in the nodal society for the next millenium The current organization are already beginning to face the key challenge which will be a factor determining the success of the new companies of the 21st Century: competition based on mobilizing the full capacity of the people involved in the company or its environment, as well as the complete corpus of knowledge acquired. From the simple, and fortunately now distant, organization relationship set out by Fayol we are currently moving towards a much richer, more complex and multi-level business environment , as it is converting the individual into the central node of a tight web of relationships within the framework of the company, and the company itself into the node of a relational network included by other companies and individuals, functioning both as clients and as the suppliers of products and services. Monday 11:00-13:00 MB00 Tutorial Chair: Saul I. Gass Venue: Aula Master Thomas L. Saaty (University of Pittsburgh) : The analytic network decision process with dependence and feedback Decision making is the most central and pervasive human activity, intrinsic in our biology and done both consciously and unconsciously. We need it to survive. Everybody makes decisions all the time. Young and old, educated and uneducated, with ease or with great difficulty. Making a decision is not just a question of selecting a best alternative. Often one needs to prioritize all the alternatives for resource allocation, or to combine the strengths of preferences of individuals to form a collective preference. Applying mathematics to decision making calls for ways to quantify or prioritize personal or group judgments that are mostly intangible and subjective. Decision making requires doing what is traditionally thought to be impossible, comparing apples and oranges. But we can compare apples and oranges by decomposing our preferences into the many properties that apples and oranges have, determining their importance to us, comparing and obtaining the relative preference of apples an oranges with respect to each property, and synthesizing the results to get the overall preference. MB00 Tutorial Chair: Graham Rand Venue: Aula Master Jacek Blazewicz (University of Technology) M. Kasprzak, M. Sterna and J. Weglarz: On some combinatorial optimization models for molecular biology Throughout the last forty years molecular biology, which aim is to study DNA construction and functioning, has emerged as a clearly defined research area with specific notions and experimental tools. It appeared however, that massive amounts of data gathered from different sources all over the world and complicated models arising in DNA analysis, required support from other research disciplines. This paper is concerned with some problems arising in the area of molecular biology that need a combinatorial optimization support. Firstly, a problem of sequencing DNA chains is studied. Sequencing algorithms for the case of negative errors are presented and some open questions are posed. Then, the DNA assembling problem is analyzed. Lastly, the problem of DNA chain alignment is discussed. Prospects of further research are also discussed. MB01: Telecommunications network design Invited Chair: Brunilde Sanso Venue: A2001 MB01.1 Patrik Soriano (HEC and CRT) B. Fortz, M. Labbe and C. Wynants: Multi-shr design for zonal networks We consider the problem of designing self-healing rings in order to protect the transmission of telecommunications demands in a zonal (regional) network. A modeling approach that takes into account ring interactions is proposed. A heuristic procedure based on tabu search is then developed for solving this very hard design problem. Preliminary computational results should be presented. MB01.2 Michel Gendreau (Université de Montreal) J. F. Larochelle and B. Sanso: A tabu algorithm for the Steiner tree problem in graphs The Steiner tree problem in graphs is a well known hard combinatorial problem that is found in many applications, in particular, as a subproblem for telecommunications network design and synthesis. In this talk we present a tabu approach to solve the problem. Extensive computational results comparing the approach with exact and heuristic algorithms will be provided. MB01.3 Brunilde Sanso (Ecole Polytechnique de Montreal) : Issues in ATM network design ATM(Asynchronous Transfer Mode) is a transfer protocol that will be used as the basis for broadband multiservice applications. In this talk we discuss the implications of this new technology in the area of operations research, in particular in what concerns network design problems. MB01.4 Luis E. Gouveia (Universidade de Lisboa) E. Janssen: Designing reliable tree networks with two cable technologies In this talk we introduce a minimum spanning tree problem with generalized hop constraints. The problem is concerned with reliability constraints in a centralized network design problem where two cable technologies are available. We present a lagrangean relaxation scheme derived from a directed multicommodity flow model. We show that the theoretical best bound associated to such scheme strictly dominates the LP bound associated to the original model. The use of a lagrangean heuristic indicates that for a set complete graphs with up to 40 nodes most of the proposed lower bounds are optimal. MB01.5 Javier Barbas (E.T.S.I. Aeronáuticos) A. Marín and A. Nitchiporenko: Lagrangean relaxation applied to multilevel facilities location problem The location of concentrators and the corresponding assignments in a star topology with maximum flow restrictions are decided at each level. Other side constraints are the maximum assignment distance and the maximum number of located concentrators. The model is solved by Lagragean relaxation of the assignment restrictions and applying a subgradient optimization algorithm. The Lagragean relaxation separates the model in so much submodels like levels are considered. Each level submodel is separated in an assignment and a location submodel. An heuristic algorithm has been developed in order to produce a feasible solution and a good set of Lagrangean multipliers. MB02: Financial modeling II Invited Chair: Constantin Zopounidis Venue: A2002 MB02.1 Stavros Zenios (University of Cyprus) A. Consiglio: High performance computing for the computer aided design of financial products This paper develops a framework for the computer aided (CAD) design of innovative financial products. The problem is broken down to questions of designing the financial products, specifying the debt structure with the amount issued in each product, and determining an optimal level of financial leverage. A hierarchy of optimization models is formulated to provide constructive answers to these issues. Input data for the models are obtained from Monte Carlo simulation procedures that generate scenarios of holding period return of the designed products. High performance computers provide the enabling technology for the implementation of the models. MB02.2 Miguel A. Rodríguez Fernández (Universidad de León) E. López, F. Herrera and C. Mendaña : The balanced financial allocation within a budget with fuzzy genetic systems Financial Resources Assignment within a Budget faces with lots of situations extremely complex which in some cases have not a satisfying solution. That is the case of financial resources allocation when the decision maker have to maximize the total utility and exist the possibility of relation among the areas utility obtained from the decision taken. Traditional tools have attempted to approximate to that exposition, however reality shows that the results have not been relevant in practice. This states the interest about whether the fuzzy logic and intelligent technologies might reach better solutions. One of the available alternatives are the Genetic Algorithms due to their capability to facilitate solutions to optimization of complex problems. In this way, with this essay we pretend to achieve solutions to the problems of financial resources allocation in a uncertainty and complementary environment applying a Fuzzy Genetic Algorithm which allows us to optimize the investment total utility. MB02.3 Theodore Trafalis (University of Oklahoma) N. P. Couellan: Feedforward supervised neutral networks for stock price prediction Modeling by using neural network are being applied to several other applications in addition to traditional areas such as pattern recognition and control. The nonlinear and smooth interpolation capabilities of neutral networks make them more powerful over standard expert systems for solving certain problems like accurate prediction of stock prices. In this paper we investigate the use of feedforward supervised neural networks to predict stock closing prices. Two neural networks models are presented. The first model is trained using stock price patterns only. The second model employs several market parameters such as interest rate, Dow Jones industrial averages, etc., to predict the next day's close price. MB02.4 N. Hicks Pedrón (Cambridge University) M. A. H. Dempster et al.: Comparison of current portfolio management techniques This paper describes the results of a recently completed study sponsored by the Frank Russell Company which compared the performance of alternative asset allocation models fitted to recent US financial market data. The basic Markowitz, fixed-mix, optimal control
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