It is now generally accepted that the 'central genome dogma' (i.e. a causal chain going from DNA to RNA to proteins and downstream to biological functions) should be replaced by the 'fluid genome dogma', that is, complex feed-forward and feed-back cycles that interconnect organism and environment by epigenomic programing - and reprograming - throughout life and at all levels, sometimes also dow...

Linear programming algorithms have been widely used in Decision Support Systems. These systems have incorporated linear programming algorithms for the solution of the given problems. Yet, the special structure of each linear problem may take advantage of different linear programming algorithms or different techniques used in these algorithms. This paper proposes a web-based DSS that assists dec...

In computational complexity theory, a decision problem is NP-complete when it is both in NP and NP-hard. Although a solution to a NP-complete can be verified quickly, there is no known algorithm to solve it in polynomial time. There exists a method to reduce a SAT (Satifiability) problem to Subset Sum Problem (SSP) in the literature, however, it can only be applied to small or medium size probl...

C. A. R. Hoare, N. Wirth, E. W. Dijkstra, and some others active in structured programing have described and tacitly recommended a hierarchical accessibility of passed data in structured programing (see for example, References 11 and 26). This fits well, they and others indicate, with both the theory and the practice of structured programing (see for example, References 15, 18, 19, and 25). Thi...

In this dissertation we study strategy iteration (also known as policy iteration) algorithms for solving Markov decision processes (MDPs) and twoplayer turn-based stochastic games (2TBSGs). MDPs provide a mathematical model for sequential decision making under uncertainty. They are widely used to model stochastic optimization problems in various areas ranging from operations research, machine l...

In an earlier paper the authors studied simplex codes of type α and β over Z4 and obtained some known binary linear and nonlinear codes as Gray images of these codes. In this correspondence, we study weight distributions of simplex codes of type α and β over Z2s . The generalized Gray map is then used to construct binary codes. The linear codes meet the Griesmer bound and a few non-linear codes...

Mixed-Initiative Systems (MIS) are hybrid decision systems where collaboration is possible between humans and machines. However, current systems sometimes override user preferences when provided with new ones. We studied linear optimization problems, where the decision maker is specifying preferences for variable values through an iterative process. We proposed a goal programming framework to d...

Parallelizing sparse simplex algorithms is one of the most challenging problems. Because of very sparse matrices and very heavy communication, the ratio of computation to communication is extremely low. It becomes necessary to carefully select parallel algorithms , partitioning patterns, and communication optimization to achieve a speedup. Two implementations on Intel hypercubes are presented i...

G. Parisi predicted an important variational formula for the thermodynamic limit of the intensive free energy for a class of mean field spin glasses. In this paper, we present an elementary approach to the study of the Parisi functional using stochastic dynamic programing and semi-linear PDE. We give a derivation of important properties of the Parisi PDE avoiding the use of Ruelle Probability C...

Although the Simplex Method (SM) developed for Dantzig is efficient for solving many linear programming problems (LPs), there are constructions of hard linear programs as the Klee-Minty cubes and another deformed products, where this method has an exponential behavior. This work presents the integration of genetic algorithms (GA) and SM to fastly reach the optimum of this type of problems. This...