Search

The Vehicle Routing Problem with Loading Constraints (VRPLC) is strongly related to real life applications in distribution logistics. It addresses the simultaneous loading and routing of vehicles, which are two crucial activities in transportation. Since treating these operations separately may result in impractical solutions, the development of applications for VRPLCs has gained the attention of researchers in recent years. Several heuristic methods have been proposed, but they consider only a limited group of practical characteristics that arise in real world situations. This study proposes a hybrid heuristic method based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic and the Clarke and Wright Savings algorithm, to solve a VRPLC with several loading and routing constraints that have not been considered simultaneously before. Experimental results show that the proposed procedure produces competitive solutions in short processing times. Lastly, the impact of the added operational constraints is also analyzed.

This paper addresses the stochastic permutation flow shop problem (SPFSP) in which the stochastic parameters are the processing times. This allows the modeling of setups and machine breakdowns. Likewise, it is proposed a multi-objective greedy randomized adaptive search procedure (GRASP) coupled with Monte-Carlo Simulation to obtain expected makespan and expected tardiness. To manage the bi-objective function, a sequential combined method is considered in the construction phase of the meta-heuristic. Moreover, the local Search combines 2-optimal interchanges with a Pareto Archived Evolution Strategy (PAES) to obtain the Pareto front. Also, some Taillard benchmark instances of deterministic permutation flow shop problem were adapted in order to include the variation in processing times. Accordingly, two coefficients of variation (CVs) were tested: one depending on expected processing times values defined as twice the expected processing time of a job, and a fixed value of 0.25. Thus, the computational results on benchmark instances show that the variable CV provided lower values of the expected makespan and tardiness, while the con-stant CV presented higher expected measures. The computational results present insights for further analysis on the behavior of stochastic scheduling problems for a better approach in real-life scenarios at industrial and service systems.

Patient Bed Assignment (PBA) consists of assigning patients to hospital beds according to specific requirements such as patient diagnosis, equipment requirements, age and gender policies, among others. We worked in conjunction with the Hospital Universitario San Ignacio (HUSI) with the goal of designing an application to support decision-making during the bed assignment process. We introduced a mathematical model for the PBA. We used Analytic Hierarchy Process (AHP) to determine the weights attributed to each part of the objective function. Due to the long execution time required, we used a Greedy Algorithm and Tabu Search (TS) to optimize the match between the patient’s requirements and the characteristics of the assigned bed. To test the algorithms, we created 15 test instances of various sizes. The results showed that the gap between the value of the objective function resulting from using the Greedy/TS in comparison with the optimal solution is on average 6.2%. Also, the TS takes 84% less time than the MILP for medium and large instances. We collected data from real life instances and compared the actual method with the designed metaheuristic. On average, the value of the objective function resulting from using the proposed Greedy/Tabu algorithm is 8.6% higher.

International audience; The SOHOMA Workshop series on Service Orientation in Holonic and Multi-Agent Manufacturing is a set of events aiming at fostering innovative research and practices in smart and sustainable manufacturing and logistics systems. The SOHOMA scientific community promotes the development of theories, methods, solutions, proof of concepts and implementations for the digital transformation of the industry of the future through intelligence distribution in service-oriented, holonic and agent-based systems. During ten editions, the workshops have gathered hundreds of researchers and practitioners that have presented their world-wide scientific contributions, published in the Springer book series “Studies in Computational Intelligence”. This paper presents an overview of the publication of the SOHOMA workshop proceedings by using a bibliometric analysis and identifies leading research and innovation trends generated by the SOHOMA community in the last ten years.

Immobilized Pichia pastoris X33/pGAPZαA-LaccPost-Stop in Ca2+ alginate beads was employed for Pleurotus ostreatus rPOXA 1B laccase batch production. Sequential statistical improvement was achieved through Plackett-Burman (PBED), (PBED-T11, 29.5±0.8 UL-1), which allowed to increase activity by 2.36-fold (12.5±2.6 UL-1) obtained in a preliminary study. Following, Box-Behnken Experimental Design (BBED) was implemented and obtained enzymatic activity in PBED-T11 was further increased by 33.5-fold (BBED-T12 989.31±187.45 UL-1). After BBED-T12 extrapolation to column, cell release remained high. To demonstrate laccase was not acting on Ca2+ alginate polymer, it was shown that both untransformed P. pastoris and S. cervisiae were able to be released from the alginate matrix and proliferate. Molecular docking evaluating interaction between rPOXA 1B and Ca2+ alginate, exhibited weak interactions between the active center and Ca2+ alginate polymer. Moreover, the active center conformation was not appropriate for ligand transformation. Immobilization conditions decreasing cell release (17.01±0.12 gL-1) allowed for high enzymatic activity (1,453.93±0.43 UL-1) with greater specific activity (18.33 Umg-1). These conditions were: 4% Na2+ alginate (w/v) and 0.3 M CaCl2, suggesting that Na2+ alginate and CaCl2 concentrations can control cell release from this matrix.

Nowadays, industries cope with a wide range of situations and/or perturbations that endanger the manufacturing productivity. Traditionally, manufacturing control systems are responsible for managing the manufacturing scheduling and execution, as these have the capability of maintaining the production operations regardless of a given perturbation. Still, the challenge of these systems is to achieve an optimal performance after the perturbations occur. For this reason, manufacturing control systems must incorporate a mechanism with intelligent capabilities to look for optimal performance and operation reactivity regardless of any scenario. This paper proposes a generic control strategy for a manufacturing control system for piloting the execution of a dynamic scheduling problem, considering a new job arrival as the manufacturing perturbation. The study explores a predictive-reactive approach that couples a genetic algorithm for the predictive scheduling and an adaptive genetic algorithm for reactivity control aiming to minimize the weighted tardiness in a dynamic manufacturing scenario. The results obtained from this proposal verify that the effectiveness was improved by using adaptive metaheuristic in a dynamic scheduling problem, considering absorbing the degradation caused by the perturbation.

This work studies the scheduling of elective procedures, with stochastic durations, in surgery rooms. Given a set of rooms with limited availability and a set of procedures, it must be decided in which room and when each procedure will be performed. The problem’s objectives are to maximize the use of the operating rooms and to minimize the delays in starting the scheduled surgeries. A simulation-optimization approach is proposed. First, procedures’ durations are modeled as random variables and a set of test percentiles (i.e. it is assumed that all surgeries will last as many minutes as the 75th percentile of its probability density function) is selected. Subsequently, using these durations as a parameter, a greedy randomized adaptive search procedure (GRASP) is run. Consequently, as many solutions as selected test percentiles are generated. Finally, a Monte Carlo simulation is used to estimate three indicators: i) rooms utilization, ii) percentage of surgeries that had delays, and iii) average delay time of scheduled surgeries. The technique was tested by solving the elective procedures scheduling problem in a high-complexity hospital in Bogota. This hospital has 19 operating rooms and 35,000 surgeries performed annually. Currently, the scheduling process is manual. The simulation-optimization proposed approach allowed to determine the relation between utilization rate and delays in the service. As the occupation percentage increases, delay times also augment, implying a reduction of the service level. An average reduction of 5% in delay times entails a reduction between 3% and 9% of operating room occupancy.

En este artículo se estudia el problema de Red de Transporte, usualmente conocido como TNDP (Transit Network Design Problem) multiobjetivo. Este consiste en encontrar la combinación ideal de rutas y frecuencias, que permita realizar un balance entre los intereses de los usuarios y los opera-dores, que se contraponen. Utiliza como datos de entrada un grafo con sus respectivos costos de transporte (en este caso tiempos) y demandas aso-ciadas a cada par de nodos. Como método de solución a este problema de optimización combinatoria multiobjetivo, se propone el uso de la metaheurística Búsqueda en Vecindades Variables (VNS), que resuelve problemas de optimización buscando soluciones competitivas mediante el cambio de vecindario iterativamente. El método propuesto fue probado inicialmente en el caso de estudio diseñado por Mandl, que consiste en 15 nodos y 21 arcos, y una matriz de demandas simétrica; y posteriormente para otras 11instancias con tres tamaños de grafo diferentes (15, 30, 45 nodos). El modelo primero se corrió con el caso original para compararlo con autores que en oportunidades pasadas han trabajado el mismo problema. Posteriormente el VNS propuesto se probó con un modelo de demanda cambiante en 3momentos del día (Mañana, tarde y noche) para corroborar los resultados positivos obtenidos en el primer ejercicio y darle un alcance mayor a la solución del problema., In this paper we study the Tranport Network Design Problem (TNDP). It consists in finding the ideal combination of routes and frequencies that allow the decision maker to balance the interests of the users and the transit operators, which are opposite. The TNDP uses as input a graph, with their transportation costs (in this case time), and the demands associated to each pair of nodes. Our proposed approach to solve the TNDP is based on a Variable Neighborhood Search (VNS) metaheuristic. VNS has been used to solve different kinds of combinatorial optimization problems and it consists in searching competitive solutions by iterative changes of the neighborhood. The VNS is tested first for the case study designed by Mandl, which consists in 15 nodes and 21 arcs, and a symmetric demand matrix. Posteriorly the VNS was tested for other 11 instances of (15, 30 and 45 nodes). In the first place, the model was run for that original case to compare it with other authors who worked this problem in the past. Then, we tested the VNS approach for a changing demand model in 3 moments of the day (Morning, afternoon and night) to prove the positive results obtained in the first exercise and give a greater scope to the problem solution., 1 Escuela Colombiana de Ingeniería Julio Garavito, Natalia.garzon-s@mail.escuelaing.edu.co, http://orcid.org/0000-0002-4217-1110, Bogotá, Colombia. 2 Pontificia Universidad Javeriana, eliana.gonzalez@javeriana.edu.co, http://orcid.org/0000-0002-4590-3401, Bogotá, Colombia. 3 Escuela Colombiana de Ingeniería Julio Garavito, ignacio.perez@escuelaing.edu.co,Bogotá, Colombia.

This study aims at determining if a collection of 16 motor tests on a physical simulator can objectively discriminate and evaluate practitioners' competency level, i.e. novice, resident, and expert.An experimental design with three study groups (novice, resident, and expert) was developed to test the evaluation power of each of the 16 simple tests. An ANOVA and a Student Newman-Keuls (SNK) test were used to analyze results of each test to determine which of them can discriminate participants' competency level.Four of the 16 tests used discriminated all of the three competency levels and 15 discriminated at least two of the three groups (α= 0.05). Moreover, other two tests differentiate beginners' level from intermediate, and other seven tests differentiate intermediate level from expert.The competency level of a practitioner of minimally invasive surgery can be evaluated by a specific collection of basic tests in a physical surgical simulator. Reduction of the number of tests needed to discriminate the competency level of surgeons can be the aim of future research.Este estudio pretende determinar si una colección de 16 pruebas en un simulador físico puede discriminar y evaluar objetivamente el nivel de competencia de practicantes de cirugía laparoscópica (novato, resistente y experto).Se realizó un diseño de experimentos con tres grupos de estudio (novatos, residentes y expertos) para probar el poder de discriminación de 16 pruebas simples. Un ANOVA y un test de Student Newman-Keuls (SNK) fueron empleados para analizar los resultados de cada prueba con el fin de determinar cuáles de ellas podían discriminar los niveles de competencia de los participantes.Cuatro de las 16 pruebas evaluadas lograron discriminar los tres niveles de competencia, y 15 pruebas lograron discriminar al menos dos de los tres grupos (α= 0.05). Adicionalmente, otras dos pruebas diferenciaron los novatos de los residentes, y otras siete pruebas diferenciaron los residentes de los expertos.El nivel de competencia de un practicante de cirugía mínimamente invasiva puede ser determinado mediante una colección de pruebas básicas en un simulador quirúrgico físico. El diseño de pruebas que discriminen los tres niveles de competencia y reduzcan el número de pruebas de la colección son posibles temas para nuevos trabajos.

This paper addresses the scheduling problem in a Permutation Flow Shop (PFS) environment, which is associated with many types of industries such as chemical, petrochemical, automobile manufacturing, metallurgical, textile, etc. Thus, this work intends to solve a PFS scheduling problem in order to minimize the total weighted tardiness, since it is an important sequencing criterion not only for on time delivery jobs but also for customer satisfaction. To solve the problem, GRASP (Greedy Randomized Adaptive Search Procedure) metaheuristic is proposed as a solution, which has shown competitive results compared with other combinatorial problems. In addition, two utility functions called Weighted Modified Due Date (WMDD) and Apparent Tardiness Cost (ATC) are proposed to develop GRASP. These are based on dynamic dispatching rules and also known for solving the problem of total weighted tardiness for single machine scheduling problem. Next, an experimental design was carried out for comparing the GRASP performance with both utility functions and against the WEDD dispatching rule results. The results indicate that GRASP-WMDD could improve the total weighted tardiness in 47.8% compared with WEDD results. Finally, the GRASP-WMDD performance for the PFS total tardiness problem was evaluated, obtaining a relative deviation index of 13.89% and ranking the method over 26 heuristics and metaheuristics.

Article history: Received November 4 2015 Received in Revised Format April 6 2016 Accepted April 7 2016 Available online April 7 2016 This paper tackles an extension to the Multi-activity Combined Timetabling and Crew Scheduling Problem (MCTCSP). The goal of the original problem is to schedule the minimum number of homogenous workers required, in order to visit a set of customers characterized by services needed against schedule availability. However, since in home services it is common to have specialized workers, a mathematical model considering a heterogeneous workforce is proposed. As a solution, a GRASP-based algorithm is designed. In order to test the metaheuristic performance, 110 instances from the literature are adapted to include categorical skills. In addition, another 10 instances are randomly generated to consider large problems. The results show that the proposed GRASP finds optimal solutions in 46% of the cases and saves 40–96% computational time. © 2016 Growing Science Ltd. All rights reserved

28 páginas Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of configuration includes assembly lines and the chemical, electronic, food, and metallurgical industries, among others. Scheduling has been mostly investigated for the deterministic cases, in which all parameters are known in advance and do not vary over time. Nevertheless, in real-world situations, events are frequently subject to uncertainties that can affect the decision-making process. Thus, it is important to study scheduling and sequencing activities under uncertainties since they can cause infeasibilities and disturbances. The purpose of this paper is to provide a general overview of the FS scheduling problem under uncertainties and its role in production logistics and to draw up opportunities for further research. To this end, 100 papers about FS and flexible flow-shop scheduling problems published from 2001 to October 2016 were analyzed and classified. Trends in the reviewed literature are presented and finally some research opportunities in the field are proposed.

Modern manufacturing systems are composed of several stages. We consider a manufacturing environment in which different parts of a product are completed in a first stage by a set of distributed flowshop lines, and then assembled in a second stage. This is known as the distributed assembly permutation flowshop problem (DAPFSP). This paper studies the stochastic version of the DAPFSP, in which processing and assembly times are random variables. Besides minimizing the expected makespan, we also discuss the need for considering other measures of statistical dispersion in order to account for risk. A hybrid algorithm is proposed for solving this NP -hard and stochastic problem. Our approach integrates biased randomization and simulation techniques inside a metaheuristic framework. A series of computational experiments contribute to illustrate the effectiveness of our approach.

Introducción: debido a las crecientes limitaciones éticas y de recursos en el entrenamiento de aprendices en cirugía mínimamente invasiva (cmi, e. g. laparoscopia) en pacientes, se pretende evaluar el efecto de la práctica continua con un videojuego en particular en el desarrollo de las habilidades fundamentales a la hora de ejecutar una de estas cirugías. Materiales y métodos: se seleccionaron tres actividades esenciales (corte, sutura y coordinación mano-ojo) por realizar en simuladores laparoscópicos, con el fin de establecer si la práctica con el videojuego es efectiva en el desarrollo de las habilidades necesarias en cmi. Se evaluaron en total ocho variables de desempeño en las tres actividades seleccionadas. Con base en esto, se evaluaron catorce aprendices médicos sin experiencia en laparoscopia, divididos en dos grupos (control e intervención), antes y después de un programa de entrenamiento estandarizado con el videojuego Marblemanía® y una duración de un mes. Resultados: se evidenció que la práctica continua con el videojuego Marblemanía® mejoró todas las variables de desempeño. Estos resultados positivos fueron significativamente diferentes a favor del grupo que tuvo acceso al programa de entrenamiento con el videojuego en 3 de las 8 variables de desempeño medidas en las tres actividades seleccionadas:errores en la actividad de sutura (p = 0,003), y el tiempo de ejecución y errores en la actividadcoordinación mano-ojo (p = 0,025 y 0,001, respectivamente). Introduction: Due to the growing economical and ethical limitations in surgeons training for minimally invasive surgery (mis, e.g. laparoscopy), this study aims at evaluating the effect of a continuous practice of a particular videogame on the development of the fundamental and specific skills needed to perform this type of procedure successfully. Materials and methods: To evaluate the effectiveness of video game practicing, three essential and common activities were chosen (cutting, suturing, and eye-hand coordination) to be performed in laparoscopic simulators. Eight different indexes or variables of performance were measured in the three activities. Fourteen voluntaries without previous experience in surgery were divided in two groups (intervention and control) and their performance was evaluated before and after a one-month standardized training program with the video game Marble Mania®. Results: A general improvement of all the performance variables was observed after one month training in the intervention group. This improvement was significant with respect to the control group in three of the eight variables: suturing errors (p = 0.003), and the execution and number of errors in the eye-hand coordination (p = 0.025 and 0.001, respectively). Introdução: devido às crescentes limitações éticas e de recursos no treinamento de aprendizes em cirurgia minimamente invasiva (CMI, e.g. laparoscopia) em pacientes, pretende-se avaliar o efeito da prática contínua com um videojogo em particular no desenvolvimento das habilidades fundamentais na hora de executar uma destas cirurgias. Materiais e métodos: se selecionaram três atividades es­senciais (corte, sutura e coordenação mão-olho), a realizar em simuladores laparoscópicos, com o fim de estabelecer se a prática com o videojogo é efetiva no desenvolvimento das habilidades necessárias em CMI. Em total, avaliaram-se oito variáveis de desempenho nas três atividades selecionadas. Com base nisso, avaliaram-se catorze aprendizes médicos sem experiência em laparoscopia, divididos em dois grupos (controles e intervenção), antes e depois de um programa de treinamento estandardi­zado com o videojogo Marblemanía® em uma duração de um mês. Resultados: se evidenciou que a pratica contínua com o videojogo Marblemanía® melhorou todas as variáveis de desempenho. Estes resultados positivos foram significativamente diferentes a favor do grupo que teve acesso ao programa de treinamento com o videojogo em três das oito variáveis de desempenho medidas nas três atividades selecionadas: erros na atividade de sutura (p = 0.003), o tempo de execução e erros na atividade coordenação mão-olho (p = 0.025 y 0.001, respectivamente). https://repository.urosario.edu.co/handle/10336/7428

El Departamento de Cirugía genera una buena parte de los ingresos de un hospital. Este estudio evalúa la variabilidad en la programación de las cirugías y cómo esta atenta contra la eficiencia del servicio. Este estudio implementó un algoritmo para la generación de dos programaciones que luego fueron comparadas con la realizada manualmente en un hospital en Colombia. Las dos programaciones generadas se diferencian entre sí al incluir o no las máximas desviaciones en los tiempos de duración de las cirugías, asumiendo que estas son causadas por factores externas al proceso y pueden ser eliminadas. Los resultados muestran que al emplear un algoritmo automático para programar las cirugías, podrían mejorarse el tiempo de respuesta y la utilización de las salas. Aún más, se pudo concluir que la variabilidad asociada a la programación manual tiene un mayor impacto que la asociada a otros factores en los indicadores de desempeño del servicio.