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The aim of this paper is to propose a procedure to create escape vectors specifically developed to perform an orthogonal projection from an Ax≤b type polyhedron's edge to its interior. The proposed procedure can be implemented in interior-point methods for solving linear programming problems since in these methods various strategies are used to avoid reaching the borders of the polyhedron. A projection procedure was developed to the polyhedron's interior starting from three scenarios and it was used on a context case demonstrating its applicability. The results show that the projection carried out in the iteration in which the escape is done not only allows abandoning from a suboptimal solution but it also kept the same objective function value. Therefore, it can be concluded that interior-point methods do not need to avoid the frontier or to adjust values, as it occurs in other applications. [ABSTRACT FROM AUTHOR]

This paper presents a study done to find an interior point in the feasible region of linear programming problems is an aspect that should be solved in the initial stage of the implementation of the interior point algorithms used to optimize them. Consequently, it is proposed a methodology that starts with a formulation that does not require adding surplus or slack variables. It only includes an additional variable to generate a polyhedron in a new expanded space and with simple projections finds an interior point in the same polyhedron. It is demonstrated that the optimal solution of the extended linear programming problem allows obtaining a feasible point of the original problem or concluding that it has no feasible solutions. [ABSTRACT FROM AUTHOR]

This paper describes a methodology to determine the optimal routes for the recollection of infectious waste in the city of Rio Cuarto in Argentina. The case can be formulated as a mixed integer linear programming problem and is classified as NP-hard. (non-deterministic polynomialtime hard). The paper proposes to improve the quality of the solutions obtained by an exact searching algorithm by mean of a local search heuristics. This technique inspects the surroundings of such solutions by different mechanisms ensuring the intensive exploitation of the promising regions of the search space. The methodology and its performance for solving different problems taken from literature and for determining a set of optimal routes are presented. [ABSTRACT FROM AUTHOR]

This paper presents an optimal budget assignment model for improving quality service in distribution systems. The model consists on a multi objective problem which aims at minimizing maintenance costs in distribution systems while maximizing the reduction of faults rate. This last objective is measured through the SAIFI indicator (System Average Interruption Frequency Index). To solve the proposed model two algorithms were implemented: NSGAII (Non-Dominated Sorting Genetic Algorithm II) and a Memetic Algorithm. Several tests were performed with two real electrical systems of 100 and 200 nodes in the Department of Antioquia in Colombia, showing the applicability of the proposed approach. The optimal Pareto fronts obtained in the problem solution show a set of available options that represent a trade-off between both objectives and provides the system operator with an estimate of how much to invest in maintenance to achieve a desired value of the SAIFI indicator. [ABSTRACT FROM AUTHOR]

This paper describes a solution method to the problem of processing n jobs on m non-related parallel machines. It is a linear and combinatorial generalized allocation problem that considered a sequencedependent setup time and dynamic job entry. A genetic algorithm with integer coding and random generation of population, parent selection, crossover and mutation is proposed. There are two descendants per generation that are compared against the worst existing element to enter to population. After a number of generations that is proportional to the product of nxm the solution is generated. The jobs are sequenced on each machine by due date and computational times are acceptable. It is concluded that the proposed genetic algorithm is an effective and efficient solution that focuses on reducing processing time and on meeting deadlines. [ABSTRACT FROM AUTHOR]

This paper presents a multiobjective analysis including variables of the environment of the energy system which is conditioned by the use of solid fuels, for this reason the analysis includes the external characteristics of the resource (fuel) of residue (ash) and the product (electricity/steam). The energy system used is Termocesar, a Colombian process for generating electricity from carbon. Three functions named thermoeconomic objective function, technology objective function and environmental objective function, are analyzed to establish the best location of the energy The genetic algorithm method is used for the optimization of the system. The results were analyzed for nine combinations of weights and show that for most of the cases the optimum includes coals from the Department of Cesar in Colombia. [ABSTRACT FROM AUTHOR]

This paper studies the effect of the mass percentage of the catalyst and the molar ratio oil:alcohol for different alcohol-catalyst systems, in the optimization of alkyl esters production from crude palm oil. Factorial design 32 and response surface methodology were used and quadratic polynomial equations by a multiple regression analysis were obtained. The evaluated answer was the percentage of conversion to glycerine using the norm of the American Oil Chemists' Society, AOCS Ca 14-56. The two variables significantly affect the conversion and the molar ratio effect is larger than the effect of the amount of catalyst. Optimum conditions vary for each system, but in general for the homogeneous catalysts the mass percentage of the catalyst is smaller (1 to 2%) than for heterogeneous (5 to 6%) and large molar ratio are required (1:12-1:40). The properties of fuel obtained are according to American standard requirements for biodiesel. [ABSTRACT FROM AUTHOR]

To improve the quality of service in cell systems, techniques of Dynamic Assignment Channels are used to reduce the probability of blocking calls. In this paper an algorithm of assignment channels is required to reduce the probability of blocking, extending the system capacity to add new calls. This is obtained by using an interchange of channels of current calls and reducing the restrictions of electromagnetic compatibility. According to this, the algorithm has to provide solutions of commitments between two different objectives; on the one hand reduce the amount of assignments, and on the other to do the same with the level of interference due to the flexible restrictions of electromagnetic compatibility. A heuristic focus based on the evolution paradigm is presented to solve the multi-objective optimization problem. Two evolutionary multi-objective algorithms (SPEAII y NSGA II) are compared by the use of two different metrics. The results show that the proposed methodology can be applied to different generations of mobile communication systems. [ABSTRACT FROM AUTHOR]