Description:
Drug-drug interaction is one of the important problems of Adverse Drug Reaction (ADR). In this paper we develop an optimization approach for the study of this problem. This approach is based on drug-reaction relationships represented in the form of a vector of weights, which can be defined as a solution to some global optimization problem. Although this approach can be used for solving many ADR problems, we concentrate here only on drug-drug interactions. Based on drug-reaction relationships, we formulate this problem as an optimization problem. The approach is applied to different classes of reactions from the Australian Adverse Drug Reaction Advisory Committee (ADRAC) database.
Description:
Drug-drug interaction is one of the important problems of Adverse Drug Reaction (ADR). In this paper we develop an optimization approach for the study of this problem. This approach is based on drug-reaction relationships represented in the form of a vector of weights, which can be defined as a solution to some global optimization problem. Although this approach can be used for solving many ADR problems, we concentrate here only on drug-drug interactions. Based on drug-reaction relationships, we formulate this problem as an optimization problem. The approach is applied to different classes of reactions from the Australian Adverse Drug Reaction Advisory Committee (ADRAC) database.
Description:
Several clustering methods based on optimisation have been developed recently. One of them is based on minimisation of the cluster function. This function is nonsmooth, nonconvex and extremely multi extremal. Minimisation of such functions is a challenging task. This process can be also very time consuming, especially if the dimension of the corresponding optimisation problem and the size of the dataset are large. In this paper we propose an approach which allows one to run programs in parallel using several CPUs simultaneously. We discuss several possible ways for design parallel implementations for the program and present results of numerical experiments.
Description:
The degree/diameter problem is to determine the largest graphs or digraphs of given maximum degree and given diameter. This paper deals with directed graphs. General upper bounds, called Moore bounds, exist for the largest possible order of such digraphs of maximum degree d and diameter k. It is known that simulated annealing and genetic algorithm are effective techniques to identify global optimization solutions. This paper describes our attempt to build a Hybrid Simulated Annealing and Genetic Algorithm (HSAGA) that can be used to construct larger digraphs, and displays our preliminary results obtained by HSAGA.
Description:
We consider the NP Hard problem of online Bin Packing while requiring that larger (or longer) items be placed below smaller (or shorter) items --- we call such a version the {LIB} version of problems. Bin sizes can be uniform or variable. We provide analytical upper bounds as well as experimental results on the asymptotic approximation ratio for the first fit algorithm.
Description:
We consider the NP Hard problem of online Bin Packing while requiring that larger (or longer) items be placed below smaller (or shorter) items --- we call such a version the {LIB} version of problems. Bin sizes can be uniform or variable. We provide analytical upper bounds as well as experimental results on the asymptotic approximation ratio for the first fit algorithm.
Description:
The purpose of the paper is to develop and study new techniques for global optimization based on dynamical systems approach. This approach uses the notion of relationship between variables which describes influences of the changes of the variables to each other. A numerical algorithm for global optimization is introduced.
Description:
A popular apprach for solving complex optimization problems is through relaxation: some constraints are removed in order to have a convex problem approximating the original problem. On the other hand, direct approaches for solving such problems are becoming increasingly powerful. This paper examines two cases drawn from data analysis, in order to compare the two techniques.
Description:
A popular apprach for solving complex optimization problems is through relaxation: some constraints are removed in order to have a convex problem approximating the original problem. On the other hand, direct approaches for solving such problems are becoming increasingly powerful. This paper examines two cases drawn from data analysis, in order to compare the two techniques.