A sequential scheduling method for multi-objective, flexible job-shop scheduling problem (FJSP) work calendars is proposed. Firstly, the sequential scheduling problem for the multi-objective FJSP under mixed work calendars was described. Secondly, two key technologies to solve such a problem were proposed: one was a time-reckoning technology based on the machine’s work calendar, the other was a sequential scheduling technology. Then, a non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) was designed to solve the problem. In the algorithm, a two-segment encoding method was used to encode the chromosome. A two-segment crossover and mutation operator were used with an improved strategy of genetic operators therein to ensure feasibility of the chromosomes. Time-reckoning technology was used to calculate start and end time of each process. The sequential scheduling technology was used to implement sequential scheduling. The case study shows that the proposed method can obtain an effective Pareto set of the sequential scheduling problem for multi-objective FJSP under mixed work calendars within an acceptable time.
The impact of target centre indices determined by the desires and selection preferences of decision makers (DMs) on target centre distances (TCDs) has been discussed extensively. One way of facilitating this is by using a multiple-attribute grey target decision method (GTDM), where normalisation plays an important role. So far, however, TCDs have only undergone linear normalisation. Therefore, we investigated the available normalisation methods with regard to the impact of a variable target centre on TCDs and objective weights. Our work shows that existing normalisation methods can be divided into two kinds: those that affect the index TCDs and determine the objective weights and those that do not, with target centre indices instead determined by the preferences of DMs. Finally, numerical examples are provided and applications are discussed.
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