Abstract
Abstract On the basis of the distinct characteristics of steel tube production process, the production scheduling problem of seamless steel tubes is described as flexible job-shop scheduling problem. Considering the parallel machines with capacity and speed constraint, maintenance of machines as well as intermediate inventory restriction, it is formulated as mixed-integer-programming(MIP) model to decide the flexible routes for every job and to optimize the sequence of jobs. The objective is not only to reduce delivery delay, but also to minimize idleness of machines and interruption in production. Given the problem is NP-hard (non-deterministic polynomial-time hard), modified genetic algorithm is proposed, whose effectiveness can be well verified in scheduling decision support system for the production of seamless steel tubes in Baoshan Iron & Steel Complex.
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