In this study, we address the current issues that usually manifest during the programming of university courses, classified as University Course Timetabling Problem, which is considered as a NP-hard problem due to the high computational demand that it requires.To solve the problem, a Mixed Integer Linear Programming model is proposed, which serves as a reference when dimensioning the problem and the restrictions that must be considered. Next, a hybrid metaheuristic method is designed based on the HGATS algorithm, Hybrid Genetic Algorithm Tabu Search Approach, developed by [16], which combines the diversification capacity of the Genetic Algorithm with the strategy of intensification of the Tabu Search Algorithm. Finally, the validation of the proposed algorithm is performed using the data from the programming of the classes from the academic periods 2018-1 and 2018-2 for the academic program of Industrial Engineering at the Industrial University of Santander, obtaining interesting solutions in a reasonable computational time, being that the process of organizing the schedule by the coordinator can last from hours to days, depending on your ability.
Dado que la programación de turnos de enfermería (NSP) es un componente esencial en la calidad del servicio de salud, y debido al gran número de investigaciones desarrolladas sobre NSP en la literatura, se desarrolla una revisión de literatura sobre los artículos sobre NSP realizados desde 2003 hasta la fecha. A partir de este trabajo, se logran identificar la tendencia y las necesidades propias de este problema, las cuales se caracterizan por (1) la necesidad de cerrar la brecha entre academia y práctica, mediante el desarrollo de modelos objetivos de representación del problema, y (2) desarrollar investigación sobre técnicas de solución capaces de tratar modelos de gran complejidad, sin sacrificar el recurso computacional. Este artículo presenta una revisión de literatura sobre los modelos de optimización en la programación de turnos de enfermería, publicados desde 2003 hasta la fecha. Palabras clave: logística hospitalaria; métodos de optimización; modelos de optimización; programación de turnos de enfermería.
In this paper, a model for the collection of waste electrical and electronic equipment is designed based on a problem of location and vehicle routing. Two main phases are carried out: The localization phase, in which the WEEE collection points are defined from a series of potential points, involving the novelty about the assignment of different types of devices to each of those points. And, the routing phase in which the collection routes are designed to minimize the associated costs. A case study is analyzed for the collection of WEEE in communes 6, 7 and 8 of Bucaramanga. For the localization phase, a mixed integer linear programming model is developed, which is solved with the GAMS software. The capacitated vehicle routing problem CVRP is addressed with the objective of minimizing the costs associated with the distance traveled by the vehicle for each of the assigned collection points, and a GRASP metaheuristic with local search operators is proposed as a solution technique to solve this second phase. The algorithm was programmed in MATLAB Software and validated with instances of the literature, showing good results for the defined case study.
En este trabajo se considera el problema de optimización que integra las funciones logísticas de localización, transporte e inventario multiperiodo en una red de distribución de dos escalones, denominado 2eLIRP. En este artículo se propone para su solución una nueva metaheurística híbrida, basada en Búsqueda Tabú, Algoritmos Genéticos y la heurística del Vecino más cercano. Los rendimientos de esta técnica híbrida se comparan con las metaheurísticas clásicas que tiene como base, encontrando mejores soluciones en el 96,67% de los experimentos realizados.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.