Scheduling a sequence for molding a number of castings each having different weights is an important large-scale optimization problem often encountered in foundries. In this paper, we attempt to solve this complex, multi-variable, and multi-constraint optimization problem using different implementations of genetic algorithms (GAs). In comparison to a mixed-integer linear programming solver, GAs with problem-specific operators are found to provide faster (with a sub-quadratic computational time complexity) and more reliable solutions to very large-sized (over one million integer variables) casting sequence optimization problems. In addition to solving the particular problem, the study demonstrates how problem-specific information can be introduced in a GA for solving large-sized real-world problems efficiently. © Springer-Verlag 2004.
CITATION STYLE
Deb, K., & Reddy, A. R. (2004). Large-Scale Scheduling of Casting Sequences Using a Customized Genetic Algorithm. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2936, 141–152. https://doi.org/10.1007/978-3-540-24621-3_12
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