Abstract

Scheduling of activities in manufacturing and service enterprises should perform efficiently, since it impacts both productivity and competitiveness. This study analyzes a real case of green wood dryers in a sawmill in Chile, with a set of ten parallel machines with three different technologies, with 161 jobs, on a monthly planning horizon. The methodology considered two stages: first, the products were grouped by density and fiber type; second, a mathematical model was proposed based on linear programming, which was modeled with AMPL software. In addition, we conducted a statistical analysis to evaluate the solution quality and the computing times, using the CPLEX and GUROBI commercial solvers. The results of the computational experiment showed a reduction in the makespan of 8.5 %, allowing us to conclude that the solver CPLEX is better than the solver GUROBI, regarding CPU time and number of instances optimally solved in 59.3 % of the analyzed cases. The most influential parameters for computing time were GUROBI cuts (evaluated at 0), CPLEX mipcuts (evaluated at 2), and repeatpresolve (evaluated at 0). The time difference in the latter parameter was statistically significant.