Abstract

A new scheduling algorithm based on improved genetic algorithm is presented to solve integrated scheduling problems in small batches of multiple complex products with different manufacturing and due dates. This algorithm virtualizes the schedule of multiple complex products into a single scheduling of one product by establishing a relationship matrix of operation of multiple products to facilitate complete optimization. In addition, novel coding, crossover, mutation, and encoding are designed for the improved genetic algorithm. The proposed integrated scheduling algorithm is tested by existing examples. Experimental results validate the effectiveness and superiority of the proposed integrated scheduling algorithm.

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