Optimization for Scheduling Identical Parallel Melting Furnaces with Non-identical Job Weights
Hu Chang-wei
Chen Xin-du
Chen Qing-xin
Mao Ning
Chen Xin
Abstract：To solve the batch scheduling problem of identical parallel melting furnaces with non-identical job weights, an optimization model is established to minimize the makespan on scheduling melting fur-naces, and the hybrid particle swarm optimization based jobs sequence (HPSO) designed.In the HPSO, particles are represented by job sequences , the batch first fit ( BFF) heuristic used to group jobs to bat-ches, the longest processing time(LPT) heuristic adopted to assign batches to batch processing machines , and the minimum completion time difference ( MCD ) heuristic proposed to optimize scheduling results by LPT heuristic .In order to avoid the premature convergence problem , the HPSO introduces the crossover and mutation operator to search for the optimal solution .Compared with SA and GA algorithm , simulation experimental results demonstrated that HPSO has a good performance .
Keywords：batch schedulingnon-identical jobsmelting furnaceparticle swarm optimization
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 73-78,85 )