Research On Low Carbon Shop Scheduling Based On Hybrid Backtracking Search Algorithm

Workshop scheduling is an important part of the manufacturing system,so the study of low-carbon shop scheduling for the realization of low-carbon manufacturing is of great significance.However the current low-carbon scheduling researches lack indicators and low-carbon scheduling solutions,while the workshop type is not rich,so the study of workshop low-carbon scheduling needs to be more deepened.In this paper,a hybrid backtracking search algorithm(HBSA)is designed to solve low-carbon scheduling problem which considers the efficiency,energy consumption and noise as the optimized objective.Finally,the validity of HBSA is verified and analyzed by designing cases with different scales.Firstly,a hybrid backtracking search algorithm(HBSA)is designed for the low-carbon scheduling problem model of permutation flow shop considering idle time energy consumption.According to the specific problems,the code/decoding,crossover and mutation and so on operators are designed to reconstruct the solution space.The backtracking search algorithm is combined with NEH,Local Search(LS)and Simulated Annealing(SA)to design a hybrid strategy.The algorithm is applied to 29 test cases,and the results obtained by HBSA are compared with branch and bound method(B&B)and genetic algorithm(GA).The results show that HBSA has better performance.Secondly,a hybrid backtracking search algorithm(HBSA)is designed for the low-carbon scheduling model of the job shop with spindle speed flexible.According to the specific problems,the code/decoding,crossover,mutation and so on operators are designed to reconstruct the solution space.Combining the backtracking search algorithm with Local Search(LS)and Simulated Annealing(SA),the hybrid strategy is designed.The algorithm is applied to three cases with different scales,and the results obtained by HBSA are compared with GA.The results show that HBSA has better performance.Then,a hybrid backtracking search algorithm(HBSA)is designed for the low-carbon scheduling problem model of flexible job shop.According to the specific problems,the code/decoding,crossover,mutation and so on operators are designed to reconstruct the solution space.Combining the backtracking search algorithm with the Local Search(LS)and Simulated Annealing(SA),the hybrid strategy is designed.The algorithm is applied to three cases with different scales,and the results obtained by HBSA are compared with GA.The results show that HBSA has better performance.Finally,we summarized the full text and forecasted the future work.