This respository contains the instances used in Borba, Ritt, Miralles, Exact and heuristic methods for solving the robotic assembly line balancing problem, Eur. J. Oper. Res., 270(1):146-156, 2018.
In robotic assembly lines, the task times depend on the robots assigned to each station. Robots are con- sidered 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 heuris- tic 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.
@Article{Borba.etal/2018,
author = {Leonardo Borba and Marcus Ritt and Cristóbal Miralles},
title = {Exact and Heuristic Methods for solving the Robotic Assembly Line Balancing Problem},
journal = {Eur. J. Oper. Res.},
year = {2018},
OPTkey = {},
volume = {270},
number = {1},
pages = {146--156},
month = oct,
doi = {10.1016/j.ejor.2018.03.011}
}