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A multi-objective optimisation algorithm for the hot rolling batch scheduling problem
Ist Teil von
International journal of production research, 2013-02, Vol.51 (3), p.667-681
Ort / Verlag
London: Taylor & Francis Group
Erscheinungsjahr
2013
Link zum Volltext
Quelle
Taylor & Francis
Beschreibungen/Notizen
The hot rolling batch scheduling problem is a hard problem in the steel industry. In this paper, the problem is formulated as a multi-objective prize collecting vehicle routing problem (PCVRP) model. In order to avoid the selection of weight coefficients encountered in single objective optimisation, a multi-objective optimisation algorithm based on Pareto-dominance is used to solve this model. Firstly, the Pareto ℳ -ℳℐ Ant System (P-ℳℳAS), which is a brand new multi-objective ant colony optimisation algorithm, is proposed to minimise the penalties caused by jumps between adjacent slabs, and simultaneously maximise the prizes collected. Then a multi-objective decision-making approach based on TOPSIS is used to select a final rolling batch from the Pareto-optimal solutions provided by P-ℳℳAS. The experimental results using practical production data from Shanghai Baoshan Iron & Steel Co., Ltd. have indicated that the proposed model and algorithm are effective and efficient.