Optimal Scheduling of Casting Sequence Using Genetic Algorithms |
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| Authors: | Kalyanmoy Deb Abbadi Raji Reddy Gulshan Singh |
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| Affiliation: | a Kanpur Genetic Algorithms Laboratory (KanGAL), Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur, Indiab Kanpur Genetic Algorithms Laboratory (KanGAL), Department of Mechanical Engineering, Indian Institute of Technology Kanpur, Kanpur 208 016, India |
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| Abstract: | Scheduling a casting sequence involving a number of orders with different casting weights and satisfying due dates of is an important optimization problem often encountered in foundries. In this article, we attempt to solve this complex, multi-variable, and multi-constraint optimization problem by using different implementations of genetic algorithms (GAs). In comparison with a mixed-integer linear programming solver, GAs with problem-specific operators are found to provide faster (with a subquadratic computational time complexity) and more reliable solutions to very large (more than 1 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 complex real-world problems. |
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| Keywords: | Scheduling Genetic algorithms Large-scale optimization Mixed-integer linear programming Knowledge-based GA Scalable optimization Subquadratic complexity |
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