A semi-flow-shop scheduling problem with processing as batches

A semi-flow-shop scheduling problem, similar to flow-shop, was presented herein. The jobs which were processed as batches on identical production line may pass certain working procedure, and go into the next directly, according to the respective technological requirements. This scheduling problem was known from the flow-shop scheduling problem. According to the actual requirements of production scheduling, the objectives considered the earliness and tardiness, as well as the idle of machine tools. An improved genetic algorithm was proposed to solve this scheduling problem. The concept of gene entropy was used for the calculation of sharing function, adaptive probabilities of crossover and mutation. These measures improve the performance of the algorithm.