A Method Applied To Flexible Job Shop Scheduling Problem With Multi-index Optimization Of Production And Energy Consumption

Flexible job shop scheduling problem(FJSP)with multi-index optimization of production and energy consumption is against the advanced manufacturing system based on the highefficiency mode,which has important practical significance in manufacturing.It balances the production resources of the workshop through comprehensive constraints,and simultaneously realizes the muti-objective optimization of production efficiency and energy allocation.This paper focuses on the multi-constrained flexible job shop scheduling problem that can reflect the complexity of production process.The evolutionary computation-based scheduling optimization control method is adopted to study the collaborative optimization of production efficiency and energy consumption.The main contents are as follows:(1)According to the characteristics of the energy consumption in the whole process,a model of flexible job shop scheduling problem with energy consumption at product level and machine level is established,which provides a theoretical basis for the subsequent problem with multi-index optimization of production and energy consumption.At the same time,combined with the characteristics and difficulties of flexible job shop scheduling problem,the basic principle,parameter configuration and algorithm characteristics of the shuffled frog leaping algorithm are analyzed in detail.Based on the study of its optimization mechanism,the advantages and disadvantages of the algorithm are summarized.(2)The model with makespan and processing energy consumption is constructed by analyzing the production resources and scheduling constraints of the flexible job shop.Optimization indexes of production and energy consumption is considered in this model.In order to reasonably arrange the processing sequence of jobs and select machines to reduce the noload energy consumption of the machine during processing,a single-parent shifting shuffled frog leaping algorithm is proposed.In addition,the local update strategy of the algorithm is improved based on multi-point crossover and single parent genetic shift operation.The experimental results demonstrate the effectiveness of this algorithm for solving such problems.(3)Taking into account to optimize makespan and energy consumption,the model of FJSP for production and multi-source energy consumption multi-index optimization is established.In addition,a turn-on/off strategy is applied to reduce the no-load time of machines and achieve better energy efficiency.Considering the complexity of multi-source energy consumption in this problem,a multi-objective shuffled frog leaping algorithm based on Pareto dominant relationship is designed to solve this problem.Due to the characteristics of multi-objective optimization algorithms,the grouping method suitable for solving this problem is adopted.The worst and the optimal solutions are updated simultaneously.The multi-objective shuffled frog leaping algorithm is used to optimize the production and energy consumption by comparing experiments with other algorithms.(4)Aiming at the scheduling mechanism and constraints of production transportation equipment,FJSP based on transportation equipment constraints is deeply studied.Since the transportation equipment is optional,flexible job shop scheduling problem needs to realize three tasks: machine allocation,process sequencing and transportation equipment selection.Therefore,a three-layer code based niched shuffled frog leaping algorithm is proposed.With the convergence optimization mechanism of the shuffled frog leaping algorithm,the introduced niche strategy can weaken the convergence in the optimization process of this algorithm,so as to obtain the scheduling scheme under different transportation time.The above method provides a theoretical method for further research of flexible job shop problem under the constraint of production and transportation equipment.