Azuma Ohuchi

Developing Support System for Sequence Design in DNA Computing

Sequence design is the important factor which governs the reaction of DNA. In related researches, the method to minimize (or maxmize) the evaluation function based on knowledge of sequence design has been used. In this paper, we develop support system for sequence design in DNA computing, which minimizes the evaluation function calculated as the linear sum of the plural evaluation terms. Our system not only searches for good sequences but also presents contribution ratio of each evaluation term to the evaluation function and can reduce the number of combination of evaluation terms by reduction of the evaluation function. It helps us to find a good criteria for sequence design in DNA computing.

Evolutionary algorithms for nurse scheduling problem

The nurse scheduling problem (NSPs) represents a difficult class of multi-objective optimisation problems consisting of a number of interfering objectives between the hospitals and individual nurses. The objective of this research is to investigate difficulties that occur during the solution of NSP using evolutionary algorithms, in particular genetic algorithms (GA). As the solution method a population-less cooperative genetic algorithm (CGA) is taken into consideration. Because contrary to competitive GAs, we have to simultaneously deal with the optimization of the fitness of the individual nurses and also optimization of the entire schedule as the final solution to the problem in hand. To confirm the search ability of CGA, first a simplified version of NSP is examined. Later we report a more complex and useful version of the problem. We also compare CGA with another multi-agent evolutionary algorithm using pheromone style communication of real ants. Finally, we report the results of computer simulations acquired throughout the experiments.

Lagrangian dual coordinatewise maximization algorithm for network transportation problems with quadratic costs

This paper gives the Lagrangian dual coordinatewise maximization (LDCM) algorithm for network transportation problems with strictly convex quadratic costs (NTPQ). An explicit expression for the dual function associated with NTPQ is obtained. Some properties of the dual function are shown. Then, using these properties, a procedure which involves successively maximizing the dual function with respect to each of its dual coordinates is applied to obtain the optimal dual solution. Then the optimal primal solution is obtained by substituting the dual solution to the simple expression. Computational results for 200 randomly generated problems reveal the effectiveness of the algorithm. The key idea of applying the Lagrangian dual method to NTPQ is that the objective function of the network problems is strictly convex. This strict convexity allows one to finesse problems that occur in using Lagrangian methods with more general problems. In particular, because the optimal solution of the Lagrangian problem is unique, the dual function is differentiable and an optimal solution to the Lagrangian with optimal multipliers is optimal in the original primal problem. These are strong results that are not true in general.

Modeling of Theme Park Problem with Multiagent for Mass User Support

We propose the Theme Park Problem as one example of test bed for mass user support. The objective of the problem’s solution is to coordinate many visiting agents’ behavior in a way that increases social welfare without reducing individual satisfaction. For the computer simulation, we design four types of basic coordination algorithms, and the simulation’s results are used to discuss the basic characteristics of the problem.

A separation method for DNA computing based on concentration control

A separation method for DNA computing based on concentration control is presented. The concentration control method was earlier developed and has enabled us to use DNA concentrations as input data and as filters to extract target DNA. We have also applied the method to the shortest path problems, and have shown the potential of concentration control to solve large-scale combinatorial optimization problems. However, it is still quite difficult to separate different DNA with the same length and to quantify individual DNA concentrations. To overcome these difficulties, we use DGGE and CDGE in this paper. We demonstrate that the proposed method enables us to separate different DNA with the same length efficiently, and we actually solve an instance of the shortest path problems.

Correction procedures for flexible interpretive structural modeling

Flexible interpretive structural modeling (FISM) is an extended and improved version of the interpretive structural modeling developed by J.N. Warfield (1974). The computer algorithm of FISM is based on the partially filled reachability matrix (PR matrix) model, an extension of the reachability matrix (R matrix) model that has great utility in all phases of ISM. While an FISM structural model is being developed, or after it has been developed, the developer may want to make changes (corrections) in it. Several types of corrections for FISM are defined: change of one or more entries from zero to one; change of one or more entries from one to zero; deletion of one or more elements and their connections; and addition of one or more elements and their connections. Four tuned-up correction procedures are proposed to provide effective and consistent corrections. The correction procedures, along with the implication procedures for a PR-matrix, give a complete set of procedures for implementing FISM. >

Implication Theory and Algorithm for Reachability Matrix Model

A reachability matrix M is a binary matrix with the reflexive and transitive property, i.e., M + I = M, and M2 = M, where I is the identity matrix. The entries of the matrix M are shown to form a multilevel implication structure derived using the transitivity property. The fundamental implication matrix P that defines this structure is derived. The matrix Q of the transitive closure of P, the complete implication matrix, is defined. It is proved that Q = p2. The problem of efficiently filling the partially filled reachability matrix is considered. An algorithm for determining all of the implied values of the unknown elements of the partially filled reachability matrix M derived from a supplied value is proposed. The algorithm requires 0(n2) computer time and 0(n2) storage, where n is the size of the matrix M. Use of the algorithm to the interpretive structural modeling (ISM) process makes it possible to do a flexible and an efficient transitive embedding.

LOCAL SEARCH BY CONCENTRATION-CONTROLLED DNA COMPUTING

Concentration-controlled DNA computing is presented for accomplishing a local search for the solution of a shortest path problem. In this method, the concentrations of DNA representing edges are determined according to the costs on edges, and then the hybridization process is performed. Since the concentrations of hopeless candidate solutions tend to be small after the hybridization process, a local search by concentration-controlled DNA computing is a promising approach. In order to discuss about the relationship between given costs on edges in the graph and concentrations of generated DNA paths, a simulation model of the hybridization process is used and the results of a laboratory experiment are shown.

Hairpin-based state machine and conformational addressing: Design and experiment

In this paper, we propose a new architecture for a multi-state DNA machine whose conformation of repeated hairpin structures changes sequentially in response to input oligomers. As an application of the machine, we also propose molecular memory in which the machine is used as a memory unit. Addressing in the memory is realized through state transitions of the machine. We then describe a method for designing DNA sequences of the machine, which exhaustively checks conformational changes of the machine by dividing its secondary structure into hairpin units. The method is based on the minimum free energy of the structure, the structure transition paths, and the total frequency of optimal and suboptimal structures. DNA sequences designed by the method were tested in a chemical experiment in which a machine consisting of two hairpins was actually constructed. As a result, we verified that the multi-state DNA machine realized the expected changes in its secondary structure.

Towards a general-purpose sequence design system in DNA computing

Sequence design has turned out to be a crucial factor in successful DNA computing. We present a support system for sequence design in DNA computing. Our system can fit various requirements for sequence design. The /spl beta/-version of this software is available for download.