Hot-rolling batch scheduling in round steel production with flexible maintenance planning

A hot-rolling batch scheduling problem of round steel with flexible maintenance planning was studied. For obtaining an effective cooperative scheduling with machine maintenance and batch production, a multi-objective integer programming model was built with the objectives to minimize the makespan, the earliness and tardiness of orders. With the consideration on the feature of the model, an improved multi-objective particle swarm optimization (IMPSO) algorithm was proposed to solve the problem. In the proposed algorithm, an insertion algorithm based on fitness assignment with chaos weighting was designed to generate the initial solution. According to the constraints in the model, some rules were proposed to repair unreasonable solutions emerging in the genetic progress of the population. With the elitist strategy, advanced individuals are preserved in evolution process, and the extremums for every individual's updating were also selected from elite set. In addition, with considering the discrete characteristic of variables, genetic operators were introduced to update particles. Experimental results show that the model and algorithm are feasible and effective.