This paper suggests a hybrid model to solve a distribution problem incorporating the impact of uncertainty in the solution. The model combines the deterministic approach and the simulation including stochastic variables such as harvest yield, loss risk and penalties/benefits to design a distribution network with the minimal cost. Through a case study that includes farmers, hubs and malt producers in the supplying chain of barley in Mexico, nine possible scenarios were analyzed to plan and distribute the harvested grain based on contract farming. This approach gets an optimal solution through an iterative process simulating the suggested solution by a mixed-integer linear programming model under uncertain conditions. The results show the convenience of maintaining the operation between four and five hubs depending on the possible scenario; besides, the variation of the levels of the barley producers’ capacities are key elements in the planning to minimize the distribution cost throughout the suggested chain
In this paper we present the multimodal interaction of two sensor systems for control of a mobile robot. These systems consist of (1) an acoustic sensor that receives and recognizes spoken commands, and (2) a visual sensor that perceives and identifies commands based on the Mexican Sign Language (MSL). According to the stimuli, either visual or acoustic, the multimodal interface of the robotic system is able to weight each sensor's contribution to perform a particular task. The multimodal interface was tested in a simulated environment to validate the pattern recognition algorithms (both, independently and integrated). The independent performance of the sensors was in average of 93.62% (visual signs and spoken commands), and of 95.60% for the multimodal system for service tasks.
Resumen. En este artículo se aborda el problema de la tardanza total ponderada en una máquina, conocido como Single Machine Total Weighted Tardiness (SMTWT, por sus siglas en inglés), reconocido en la literatura como un problema de tipo NP-duro debido a su complejidad computacional. Para su solución se hace una propuesta de algoritmo Greedy Randomized Adaptive Search Procedure (GRASP) con una estrategia de integración de los operadores de diversificación 2-opt e inversión, cuyo objetivo es la minimización de costos a través de encontrar un orden efectivo de las tareas abordadas en cada máquina. Se utilizó la biblioteca OR-Library con problemas de 40, 50 y 100 tareas con 125 instancias cada uno. El algoritmo propuesto obtuvo, para el total de casos analizados, valores que en promedio tenían un 6.5% de error respecto a los mejores valores conocidos y en aproximadamente el 15% se encontraron mejores soluciones que aquellas reportadas en la literatura.
This chapter provides a proposal for demand management in furniture SMEs located in the city of Puebla, México. The historical production data reviewed, and the classification of the most critical articles was made using the ABC classification methodology. Subsequently, the literature of SMEs was analyzed as well as the current situation and statistical information was sought. Additionally, it presented an overview of the models to forecast demand and applied to the most relevant articles. Due to the results and previous study, it was decided to implement a forecasting technique which is modelled by artificial neural networks. The ANN model developed with the TANSIGMOID transfer function by using MATLAB software. The appropriate forecasting techniques selected according to the variability of the demand of the articles takes a short-term planning horizon. This research will help the company reduce uncertainty, forecasting sales, and achieve better production planning through ANNs.
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