David Juárez-Romero

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In this paper a Memetic Algorithm (MA) is proposed for solving the Vehicles Routing Problem with Time Windows (VRPTW) multi-objective, using a constraint satisfaction heuristic that allows pruning of the search space to direct a search towards good solutions. An evolutionary heuristic is applied in order to establish the crossover and mutation between(More)
An algorithm of simulated annealing for the job shop scheduling problem is presented. The proposed algorithm restarts with a new value every time the previous algorithm finishes. To begin the process of annealing, the starting point is a randomly generated schedule with the condition that the initial value of the makespan of the schedule does not surpass a(More)
  • Instituto Politécnico, Nacional México Mosso-Vázquez, Alejo Juárez-Romero, David Cruz-Chávez, Marco Antonio, Luis Sucar +6 others
  • 2015
A one-phase efficient method to solve linear programming (LP) problems for grasp analysis of robotic hands is proposed. Our method, named as KKT Simplex method, processes free variables directly while choosing the entering and leaving variables, which makes it a one-phase method able to start at any point of the set of feasible solutions. Besides, the(More)
A one-phase efficient method to solve linear programming (LP) problems for grasp analysis of robotic hands is proposed. Our method, named as KKT Simplex method, processes free variables directly while choosing the entering and leaving variables, which makes it a one-phase method able to start at any point of the set of feasible solutions. Besides, the(More)
In this article, a toolbox based on a monitoring and control interface (MCI) is presented and applied in a heat exchanger. The MCI was programed in order to realize sensor fault detection and isolation and fault tolerance using virtual sensors. The virtual sensors were designed from model-based high-gain observers. To develop the control task, different(More)
Simulated annealing (SA) converges by means of a probability of acceptance toward a minimum value of the cost function to a minimum temperature. When the cost function is very high, the probability of acceptance is minimum when temperature descends to a minimum value, for this, the probability is controlled for the temperature. An incorrect tuning of this(More)
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