INTEC 05402
INSTITUTO DE DESARROLLO TECNOLOGICO PARA LA INDUSTRIA QUIMICA
Unidad Ejecutora - UE
artículos
Título:
A novel hybrid MILP-based solution strategy to industrial-scale AWS scheduling problems
Autor/es:
A. AGUIRRE; C.A. MÉNDEZ; P. CASTRO
Revista:
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Editorial:
ELSEVIER SCIENCE BV
Referencias:
Lugar: Amsterdam; Año: 2011
ISSN:
0377-2217
Resumen:
The Automated Wet-etch Station (AWS) is one of the most critical stages of a modern semiconductor manufacturing system (SMS), which has to simultaneously deal with many complex constraints and limited resources. Due to its inherent complexity, real-world automated wet-etch station scheduling problems are intractable by full-space mathematical formulations. Heuristic, meta-heuristics and simulation-based methods have thus been reported in the literature to provide good feasible solutions with reasonable CPU times.
This work presents a novel hybrid MILP-based decomposition strategy that joins the advantages of a rigorous MILP (Mixed Integer Linear Programming) continuous-time formulation with the flexibility of dynamic heuristic procedures. The schedule generated provides near-optimal dynamic solutions to challenging industrial-sized AWS scheduling problems with a moderate computational cost. Also, this methodology provides an important improvement in comparison with best results found in the literature for the most complex problem instances analyzed.
