Exact and heuristic methods for solving the Robotic Assembly Line Balancing Problem

[EN] In robotic assembly lines, the task times depend on the robots assigned to each station. Robots are considered an unlimited resource and multiple robots of the same type can be assigned to different stations. Thus, the Robotic Assembly Line Balancing Problem (RALBP) consists of assigning a set of tasks and a type of robot to each station, subject to precedence constraints between the tasks. This paper proposes a lower bound, and exact and heuristic algorithms for the RALBP. The lower bound uses chain decomposition to explore the graph dependencies. The exact approaches include a novel linear mixed-integer programming model and a branch-bound-and-remember algorithm with problem-specific dominance rules. The heuristic solution is an iterative beam search with the same rules. To fully explore the different characteristics of the problem, we also propose a new set of instances. The methods and algorithms are extensively tested in computational experiments showing that they are competitive with the current state of the art. (C) 2018 Elsevier B.V. All rights reserved.Borba, L.; Ritt, M.; Miralles Insa, CJ. (2018). Exact and heuristic methods for solving the Robotic Assembly Line Balancing Problem. European Journal of Operational Research. 270(1):146-156. https://doi.org/10.1016/j.ejor.2018.03.011S146156270

Solving motion planning problems

This work considers a family of motion planning problems with movable blocks. Such problem is de ned by a maze grid occupied by immovable blocks (walls) and free squares. There are k movable blocks (stones) and k fixed goal squares. The man is a movable block that can traverse free squares and move stones between them. The problem goal is to move the stones from their initial positions to the goal squares with the minimum number of stone moves. (Párrafo extraído del texto a modo de resumen)Sociedad Argentina de Informática e Investigación Operativa (SADIO

Solving motion planning problems

This work considers a family of motion planning problems with movable blocks. Such problem is de ned by a maze grid occupied by immovable blocks (walls) and free squares. There are k movable blocks (stones) and k fixed goal squares. The man is a movable block that can traverse free squares and move stones between them. The problem goal is to move the stones from their initial positions to the goal squares with the minimum number of stone moves. (Párrafo extraído del texto a modo de resumen)Sociedad Argentina de Informática e Investigación Operativa (SADIO

Capping methods for the automatic configuration of optimization algorithms

Automatic configuration techniques are widely and successfully used to find good parameter settings for optimization algorithms. Configuration is costly, because it is necessary to evaluate many configurations on different instances. For decision problems, when the objective is to minimize the running time of the algorithm, many configurators implement capping methods to discard poor configurations early. Such methods are not directly applicable to optimization problems, when the objective is to optimize the cost of the best solution found, given a predefined running time limit. We propose new capping methods for the automatic configuration of optimization algorithms. They use the previous executions to determine a performance envelope, which is used to evaluate new executions and cap those that do not satisfy the envelope conditions. We integrate the capping methods into the irace configurator and evaluate them on different optimization scenarios. Our results show that the proposed methods can save from about 5% to 78% of the configuration effort, while finding configurations of the same quality. Based on the computational analysis, we identify two conservative and two aggressive methods, that save an average of about 20% and 45% of the configuration effort, respectively. We also provide evidence that capping can help to better use the available budget in scenarios with a configuration time limit.This research has been supported by Coordenação de Aperfeiçoa-mento de Pessoal de Nível Superior – Brasil (CAPES) – Finance Code001. M. de Souza acknowledges the support of the Santa Catarina State University, Brasil. M. Ritt acknowledges the support of CNPq, Brasil (grant 437859/2018-5) and Google Research Latin America (grant25111). M. López-Ibáñez is a ‘‘Beatriz Galindo’’ Senior Distinguished Researcher (BEAGAL 18/00053) funded by the Spanish Ministry of Science and Innovation (MICINN). This research is partially funded by TAILOR ICT-48 Network (No 952215) funded by EU Horizon 2020 research and innovation programme. Funding for open access charge: Universidad de Málaga / CBU

Cardiopulmonary exercise and 6-min walk tests as predictors of quality of life and long-term mortality among patients with heart failure due to Chagas disease

Universidade Federal de São Paulo, Div Cardiol, São Paulo, BrazilSanta Izabel Hosp, Div Cardiol, Salvador, BrazilBrazilian Clin Res Inst, São Paulo, BrazilDuke Clin Res Inst, Durham, NC USAUniversidade Federal de São Paulo, Div Cardiol, São Paulo, BrazilWeb of Scienc

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the classical simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.Comment: 18 pages, 1 figur

Geographic Clustering of Leishmaniasis in Northeastern Brazil1

Different forms of this disease are spreading rapidly in distinct geographic clusters in this region