Abstract
The carton manufacturing process has several characteristics, including processing procedures, variation in type and processing procedure for each carton, specific operating machines set up by a technician, and multiple machines with different efficiencies in each workstation. Thus, decisions on pairing technicians, machines, and products and the job processing sequence production schedule arrangement have considerable influence on the efficiency of the machines and the completion time of jobs. This study establishes a mathematical model and presents an immune-based algorithm (IBA) and genetic-based algorithm (GBA) to develop a comprised assignment decision and production schedule and determine the best decisions to efficiently minimize the total tardiness cost. The proposed conversion scheme is guaranteed to produce feasible decisions considering the relationship between the encoded value of the adapted evolutionary algorithms and decisions associated with assignments and the production schedule. Numerical examples of a real case in Taiwan are solved using the proposed IBA, GBA, and CPLEX optimization solver. Computational results show that, except for cases with a few orders, the IBA method performed best, followed by the GBA method and then the CPLEX solver.
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