We study singularly perturbed linear programs. These are parametric linear programs whose constraints become linearly dependent when the perturbation parameter goes to zero. Problems like that were studied by Jeroslow in 1970’s. He proposed simplex-like method, which works over the field of rational functions. Here we develop an alternative asymptotic simplex method based on Laurent series expa...

This paper presents a novel ant colony algorithm integrating genetic algorithms and simplex algorithms. This method is able to not only speed u p searching process for optimal solutions, bu t also improve the quality of the solutions. I n this paper, the proposed method is applied to set up a learning model for the "Tuned" mask, which is used for texture classification. Experimental results on ...

The hybridization of genetic algorithms and the simplex method have been proven in literature as useful and promising in optimizations. Therefore, this paper proposes a multi-teams genetic-algorithm (MT-GA) hybrid developed toward extending the previous simplex-GA hybrids. The approach utilizes the simplex method as a united team and multi-teams collaboration and also competition search process...

An enzyme immunoassay (EIA) was developed for detecting antibody to herpes simplex virus, and the results were compared with those of complement fixation, indirect immunofluorescent-antibody, and plaque reduction neutralization tests. Test sera showed very little nonspecific reactivity even at a starting dilution as low as 1:10. EIA results showed excellent correlation with results obtained by ...

In this short paper we prove that the classic simplex method with the mostnegative-reduced-cost pivoting rule (Dantzig 1947) for solving the Markov decision problem (MDP) with a fixed discount rate is a strongly polynomial-time algorithm. The result seems surprising since this very pivoting rule was shown to be exponential for solving a general linear programming (LP) problem, and the simplex (...

This paper deals with the roundingerror analysis of the simplex method for solving linear-programming problems. We prove that in general any simplex-type algorithm is not well behaved, which means that the computed solution cannot be considered as an exact solution to a slightly perturbed problem. We also point out that simplex algorithms with well-behaved updating techniques (such as the Barte...

A little bit of reflection should convince you that the present scenario is essentially the same as that at the start of Phase II of the standard Simplex method. There is, however, a logistical difference, namely that the standard Simplex tableau associated with the current solution is not explicitly available to us. Therefore, we need to develop a different set of procedures for generating inf...

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...

The determination of the factors influencing the effectiveness of algorithm visualization poses an interesting research question. In this paper, we present the results of a longitude empirical study regarding this question. The study was based on an evaluation of the Visual LinProg educational tool inside classrooms. Visual LinProg is a web-based educational tool, which solves linear programmin...