Browsing by Author "Baesler, Felipe"
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Publication A home hospitalization assignment and routing problem with multiple time windows, mandatory returns and perishable biological samples: A Chilean case study(2024) Varas, Mauricio; Baesler, Felipe; Basso, Franco; Contreras, Juan Pablo; Pezoa, Raúl; Rojas-Goldsack, María FranciscaThe increase in life expectancy and formal care has fostered the demand for home care services, including home hospitalization. For this service, decision-makers must allocate the staff and route the visits as efficiently as possible. To tackle this problem, in this paper, we devise a new mixed-integer programming formulation that incorporates several industry-specific features, including matching patients to medical specialties and synchronized visits of multiple specialists. Moreover, the proposed formulation also includes three features that have not been tackled simultaneously in the previous literature: multiple time windows, mandatory lunch breaks at the hospital, and fast delivery of perishable biological samples. The proposed model can be reduced to a vehicle routing problem with multiple times windows, known as NP-hard. Therefore, for solving large instances, we design a heuristic procedure composed of a constructive heuristic coupled with an improvement heuristic, which builds on a local branching scheme. To test the applicability of our approach, we conduct a case study focusing on the actual operations of Hospital Padre Hurtado of Santiago, Chile. Our computational experiments show that the model provides fully implementable solutions. Moreover, the heuristic procedure provides high-quality routes (regarding quality and solution times), making it a promising alternative to experience-based scheduling methods and state-of-the-art solvers.Item Analysis of inventory strategies for blood components in a regional blood center using process simulation.(2014) Baesler, Felipe; Nemeth, Matías; Martínez, Cristina; Bastías, AlfonsoBackground The storage of blood components is an important concern in the blood supply chain. Because these are perishable products, the definition of good inventory policies is crucial to reduce shortages and spills. Study Design and Methods To analyze and propose inventory policies in a regional blood center, a discrete event simulation model was created using simulation software ( Arena 12.0, Rockwell Software). The model replicates the activities that are performed along the supply chain including donation arrivals, testing, production, inventory management, and dispatching. Results Twelve different scenarios were analyzed, with each one representing different inventory policies composed of a combination of an optimal inventory, a reorder point, and a level of extra donations. The best scenario demonstrates that it is possible to decrease unsatisfied demand and wastage of red blood cell units by 2.5 and 3%, respectively, when compared to current practices. Conclusions This study shows that simulation is an alternative that can be used to model inventory components in blood centers. A responsible selection of inventory variables can improve the capability of the system to respond to the final patient requirements.Item Desarrollo de un algoritmo para la generación y elección de soluciones de corte en la operación de canteo y despuntado en aserraderos(2011) Vergara, Francisco P.; Baesler, Felipe; Ramos, MarioIn this research work an algorithm that gathers the best procedures applied in sawmills was developed, along with a methodology based on cutting geometrical line analysis. This application was programmed under the C(++) language, sizes objective board and its prices, and the 2-D slab geometry are the input data, obtaining length and width solutions for every slab. Its outcomes have been compared with a pattern that matches the solutions provided by an "optimized" cutting machine in a southern sawmill in Chile. Four types of solutions were obtained when inputting slabs geometry, which was captured with four different reading steps. Outcomes show that solutions achieved with a reading width of 100 mm were 4% better in average than the pattern, and far better to other solutions achieved with the remaining 3 steps. Leaving aside the particular operating conditions of either method; a theoretical comparison of time by solution method, indicates that the 77 milliseconds SISCORMAD employed are significantly lower than those obtained with dynamic programming 320 milliseconds, 890 milliseconds with total enumeration, and 140 milliseconds obtained with geometric heuristic as solution times reported by [6]. This feature makes the developed algorithm very attractive for future applications. However, given the heuristic nature SISCORMAD, it is just a high quality solution, but not optimal.Item Multiobjective parallel machine scheduling in the sawmill industry using memetic algorithms(2014) Baesler, Felipe; Palma, Cristian D.This study presents a multiobjective optimization algorithm that is termed memetic algorithm with compromise search (MACS). This algorithm, proposed by the authors, combines genetic evolution with local search, in the same way as traditional memetic algorithms, but with the use of independent populations for each objective, as well as a mechanism for finding compromise solutions (tradeoffs) via a local search operator. The algorithm was applied to a parallel machine scheduling problem involving a molding production process in the wood industry. The algorithm was compared against four multiobjective techniques available in the literature: the multiobjective genetic algorithm (MOGA), the strength Pareto evolutionary algorithm (SPEA), the non-sorting genetic algorithm II (NSGA II), and multiobjective genetic local search (MOGLS). The proposed approach outperformed the benchmark techniques in most of the test problems based on two objectives of industrial interest: minimization of the maximum completion time (Cmax) and minimization of total tardiness. These objectives are directly related to the productivity of the product and the ability to deliver goods on time.Item Proceso logístico productivo de un centro de sangre regional: modelamiento y análisis(2011) Baesler, Felipe; Martínez, Cristina; Yaksic, Eduardo; Herrera, ClaudiaBackground: The blood supply chain is a complex system that considers different interconnected elements that have to be synchronized correctly to satisfy in quality and quantity the final patient requirements. Aim: To determine the blood center maximum production capacity, as well as the determination of the necessary changes for a future production capacity expansion. Material and Methods: This work was developed in the Blood Center of Concepcion, Chile, operations management tools were applied to model it and to propose improvement alternatives for the production process. The use of simulation is highlighted, which permitted the replication of the center behavior and the evaluation of expansion alternatives. Results: It is possible to absorb a 100% increment in blood demand, without making major changes or investments in the production process. Also it was possible to determine the subsequent steps in terms of investments in equipment and human resources for a future expansion of the center coverage. Conclusions: The techniques used to model the production process of the blood center of Concepcion, Chile, allowed us to analyze how it operates, to detect "bottle necks", and to support the decision making process for a future expansion of its capacity (Rev Med Chile 2011; 139: 1150-1156).Item Simulation Optimisation for Operating Room Scheduling(2015) Baesler, Felipe; Gatica Fuentes, J.; Correa, RodrigoThis paper presents a case study on operating room scheduling in a small hospital in Chile. Patient flow was represented using a discrete-event simulation model that considered the randomness associated with the primary activities of the entire process, which includes Pre- and post-hospitalisation, surgery, surgery setup and recovery. A simulated annealing algorithm was implemented and connected to the simulation model to search for better patient schedules. Additionally, three dispatching rules, Shortest Processing Time (SPT), Longest Processing Time (LPT) and First-In, First-Out (FIFO) were used. The results showed that the simulated annealing approach, based on the Cmax objective function, obtained schedules that were 18 % better than the hospital's scheduling practices. The utilisation of dispatching rules also has a significant effect in the Cmax indicator. The SPT rule performed better than the hospital schedule in two of the three experiments considered in the study.