Evolving genetic algorithm for Job Shop Scheduling problems
نویسندگان
چکیده
This paper addresses an attempt to evolve genetic algorithms by a particular genetic programming method to make it able to solve the classical Job Shop Scheduling problem (JSSP), which is a type of very well known hard combinatorial optimisation problems. The aim is to look for a better GA such that solves JSSP with preferable scores. This looking up procedure is done by evolving GA with GP. First we solve a set of job shop scheduling benchmarks by using a conventional GA and then an association of GP to evolve a GA. The instance of JSSP tackled are available in OR literature.
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