20514902
A CHIM-based interactive Tchebycheff procedure for multiple objective decision making
This study presents a new solution procedure for multiple objective programming (MOP). It applies the concept of the normal boundary intersection (NBI) within the framework of the interactive weighted Tchebycheff procedure (IWTP). The proposed procedure is a collaborative approach to overcome the weak points inherent in both the NBI method and IWTP. In order to control the solution procedure of pinpointing a final solution properly, we parameterized the Pareto-frontier via a set of reference point vectors based on the convex hull of individual maxima (CHIM) instead of using the varying weights of each objective. Using well-distributed reference point vectors, we could identify well-distributed Pareto-optimal solutions, thereby eliminating the IWTP filtering stages and reducing the chance of missing the best compromise solution from the decision maker (DM)'s utility point of view. Moreover, by working with a sequence of progressively smaller subsets of reference point vectors, the DM can identify a final solution at earlier stages than with the IWTP.
46325531
A utility range-based interactive group support system for multiattribute decision making
Abstract This research suggests an interactive procedure for solving a multiattribute group decision problem using a range-typed utility information, and develops an interactive group support system (RINGS) to implement some capabilities of the procedure. It is often difficult for group members to articulate their preferences with cardinal values, instead they prefer to give incomplete information only. Utility ranges are obtained by solving linear programming problems with incompletely specified information. RINGS finds out conflicting opinions among group members, compares each member's preferences with the others’, and suggests a direction for consensus seeking. The procedure of RINGS utilizes range-typed visual information, which helps the group reach a consensus. RINGS has several facilities like graphic user interface, model base, and database, so the total time to reach a group consensus is reduced. The evaluation of information systems is illustrated as a demonstration of some capabilities of RINGS. Scope and purpose This paper deals with the multiple attribute decision-making problem using a separable linear programming technique when group decision makers give only their incomplete information about the attribute weight and alternative value. The utility range for individual decision maker is calculated from each decision maker's incomplete information, and the utility range for group decision makers is obtained from those of individual decision makers. An interactive procedure for establishing a group's pairwise dominance relations with a group's utility range is described, and an interactive group support system (RINGS) is developed to implement the procedure. A case study about the evaluation of information systems is illustrated as a demonstration of some capabilities of RINGS.
16116503
Evolutionary programming techniques for constrained optimization problems
Two evolutionary programming (EP) methods are proposed for handling nonlinear constrained optimization problems. The first, a hybrid EP, is useful when addressing heavily constrained optimization problems both in terms of computational efficiency and solution accuracy. But this method offers an exact solution only if both the mathematical form of the objective function to be minimized/maximized and its gradient are known. The second method, a two-phase EP (TPEP) removes these restrictions. The first phase uses the standard EP, while an EP formulation of the augmented Lagrangian method is employed in the second phase. Through the use of Lagrange multipliers and by gradually placing emphasis on violated constraints in the objective function whenever the best solution does not fulfill the constraints, the trial solutions are driven to the optimal point where all constraints are satisfied. Simulations indicate that the TPEP achieves an exact global solution without gradient information, with less computation time than the other optimization methods studied here, for general constrained optimization problems.
3103350
Random Matchings in Regular Graphs
d-regular graph G, let M be chosen uniformly at random from the set of all matchings of G, and for let be the probability that M does not cover x.We show that for large d, the 's and the mean μ and variance of are determined to within small tolerances just by d and (in the case of μ and ) :
Theorem. For any d-regular graph G,
(a), so that ,
(b),where the rates of convergence depend only on d.
6458402
METIS: multiple extraction techniques for informative sentences
SUMMARY
METIS is a web-based integrated annotation tool. From single query sequences, the PRECIS component allows users to generate structured protein family reports from sets of related Swiss-Prot entries. These reports may then be augmented with pertinent sentences extracted from online biomedical literature via support vector machine and rule-based sentence classification systems.


AVAILABILITY
http://umber.sbs.man.ac.uk/dbbrowser/metis/
39277510
Lagrangian-Based Evolutionary Programming for Constrained Optimization
In this paper, Lagrangian-based evolutionary programming, Evolian is proposed for the general constrained optimization problem, which incorporates the concept of (1) multi-phase optimization process and (2) constraint scaling techniques to resolve the ill-conditioning problem. In each phase of Evolian, the typical EP is performed using augmented Lagrangian objective function with a penalty parameter fixed. If there is no improvement in the best objective function in one phase, another phase is performed after scaling the constraints, and updating the Lagrange multipliers and penalty parameter. Simulation results indicate that Evolian gives outperforming or at least reasonable solutions for multivariable heavily constrained optimization problem compared to other several evolutionary computation based methods.
62653029
The BlackWidow High-Radix Clos Network
This paper describes the radix-64 folded-Clos network of the Cray BlackWidow scalable vector multiprocessor. We describe the BlackWidow network which scales to 32K processors with a worstcase diameter of seven hops, and the underlying high-radix router microarchitecture and its implementation. By using a high-radix router with many narrow channels we are able to take advantage of the higher pin density and faster signaling rates available in modern ASIC technology. The BlackWidow router is an 800 MHz ASIC with 64 18.75Gb/s bidirectional ports for an aggregate offchip bandwidth of 2.4Tb/s. Each port consists of three 6.25Gb/s differential signals in each direction. The router supports deterministic and adaptive packet routing with separate buffering for request and reply virtual channels. The router is organized hierarchically [13] as an 8�8 array of tiles which simplifies arbitration by avoiding long wires in the arbiters. Each tile of the array contains a router port, its associated buffering, and an 8�8 router subswitch. The router ASIC is implemented in a 90nm CMOS standard cell ASIC technology and went from concept to tapeout in 17 months.