In this paper, we develop and apply a genetic algorithm to solve surgery scheduling cases in a Mexican Public Hospital. Here, one of the most challenging issues is to process containers with heterogeneous capacity. Many scheduling problems do not share this restriction; because of this reason, we developed and implemented a strategy for the processing of heterogeneous containers in the genetic algorithm. The final product was named “genetic algorithm for scheduling optimization” (GAfSO). The results of GAfSO were tested with real data of a local hospital. Said hospital assigns different operational time to the operating rooms throughout the week. Also, the computational complexity of GAfSO is analyzed. Results show that GAfSO can assign the corresponding capacity to the operating rooms while optimizing their use.

Eliciting requirements of products or solutions in informally structured domains is a highly creative and complex activity due to the inherent characteristics of these domains, such as the great quantities of tacit knowledge used by domain specialists, the dynamic interaction between domain specialists and their environment in order to solve problems, the necessity of these solutions of products to be developed by teams of specialists and the asymmetry of knowledge between domain specialists and requirements engineers. The knowledge management discipline promotes an integrated approach in order to face these challenges; therefore, a strategy for addressing requirements elicitation that incorporates techniques and methods of this discipline has been proposed as a serious approach to deal with those challenges. The valuable results of the application of the strategy in real cases prove empirical insights about its utility.

Here, we report the design of two deterministic observers that exploit the capabilities of a home-made divergent trinocular visual sensor to sense depth data. The three-dimensional key points that the observers can measure are triangulated for visual odometry and estimated by an extended Kalman filter. This work deals with a four-wheel-drive mobile robot with four passive suspensions. The direct and inverse kinematic solutions are deduced and used for the updating and prediction models of the extended Kalman filter as feedback for the robot’s position controller. The state-estimation visual odometry results were compared with the robot’s dead-reckoning kinematics, and both are combined as a recursive position controller. One observer model design is based on the analytical geometric multi-view approach. The other observer model has fundamentals on multi-view lateral optical flow, which was reformulated as nonspatial–temporal and is modeled by an exponential function. This work presents the analytical deductions of the models and formulations. Experimental validation deals with five main aspects: multi-view correction, a geometric observer for range measurement, an optical flow observer for range measurement, dead-reckoning and visual odometry. Furthermore, comparison of positioning includes a four-wheel odometer, deterministic visual observers and the observer–extended Kalman filter, compared with a vision-based global reference localization system.

In Informal Structured Domains not all concepts and their relations are formally defined, the most of the problems does not have algorithms to obtain solutions, and the domain specialists use large amounts of tacit knowledge to solve problems. These characteristics generate ambiguous, inappropriate and incomplete requirements that could increase the development time of a software system. In order to minimize these problems, we propose a Requirements Engineering strategy based on knowledge management. As a case study, the strategy was used to the development of a software system, which evaluates the cognitive impairment in patients with sclerosis multiple.