Solving stochastic programming problems via Kalman filter and affine scaling

Article Abstract:

The application of the Kalman filter in conjunction with affine scaling for solving stochastic programming problems is considered. Specifically, a state space model of affine scaling was developed to obtain the correspondences between the Kalman filter and the affine scaling algorithm. This facilitates 'a unified treatment of the estimation and optimization problems' and the derivation of a Kamarkar-based algorithm for solving stochastic linear programming problems.

Operations research, Management science, Case studies, Kalman filtering, Stochastic programming

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A genetic-based framework for solving (multi-criteria) weighted matching problems

Article Abstract:

A flexible genetic-based framework is presented and analyzed which is used for solving the multi-criteria weighted matching problem (mc-WMP). The potential of the proposed algorithm is demonstrated by comparing to a multi-objective simulated annealing algorithm.

Analysis, Algorithms, Problem solving, Algorithm

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A tabu search algorithm for maximum parsimony phylogeny inference

Article Abstract:

Application of heuristics for performance of tabu search to determine maximum parsimony during combinatorial optimization of phylogeny inference, as part of decision analysis in bioinformatical research, is described.

United States, China, Science & research, Combinatorial optimization, Heuristic programming, Computational biology

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