Abstract
As the Flexible Job Shop Scheduling Problem (or FJSP) is strongly NP-hard, using an evolutionary approach to find near-optimal solutions requires effective chromosome representations as well as carefully designed parameters for crossover and mutation to achieve efficient search. This paper proposes a new chromosome representation and a design of related parameters to solve the FJSP efficiently. The results of applying the new chromosome representation for solving the 10 jobs x 10 machines FJSP are compared with three other chromosome representations. Empirical experiments show that the proposed chromosome representation obtains better results than the others in both quality and processing time required.
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Tay, J.C., Wibowo, D. (2004). An Effective Chromosome Representation for Evolving Flexible Job Shop Schedules. In: Deb, K. (eds) Genetic and Evolutionary Computation – GECCO 2004. GECCO 2004. Lecture Notes in Computer Science, vol 3103. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24855-2_19
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DOI: https://doi.org/10.1007/978-3-540-24855-2_19
Publisher Name: Springer, Berlin, Heidelberg
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