A genetic algorithm for job shop scheduling problems with alternate routing

A two pass genetic algorithm is used to solve the job shop scheduling problem with alternate routing. The first pass picks the alternatives using a genetic algorithm, the second pass provides the order and start time of jobs on the selected alternatives by solving a nonlinear program. A nonlinear constraint reduces the dimensional complexity of the best known formulation for a job shop problem, and is used in the second pass of the algorithm. Preliminary results of this algorithm are encouraging and the algorithm has been able to solve small test problems to optimality.

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