Research On Algorithm Of Manufacturing Resource-Constrained Project Scheduling Problem

Modern manufacturing is developing from a variety of large-scale repetitive manufacturing to multi-variety of small-scale adaptive manufacturing.This development trend provides application foundation,application market and great development potential for manufacturing project management.The core of project management is to optimize project scheduling and balance resource allocation,so that project progress can be controlled more accurately during project execution,so as to shorten the construction period,save costs and improve quality.Resource-constrained project scheduling is a classic scheduling problem in the field of project management.It is necessary to arrange scheduling schemes to meet the logical constraints and resource constraints to minimize the total duration.Taking this problem as the research object,the advantages and disadvantages of various algorithms are analyzed,and a better solution method is sought and verified with practical project cases.Compare and analyze project scheduling problem solving models and algorithms.For the resource-constrained project scheduling problem,the optimal three-point time estimation method is used to calculate the activity duration;the project constraint conditions are set,including the pre-activity constraint and the renewable resource constraint;and the objective function is determined to minimize the total duration.The theoretical models and applications of classical genetic algorithm and cuckoo algorithm are studied,and the advantages and disadvantages of the two algorithms are pointed out.Redesign the encoding and decoding operations of both algorithms.An improved algorithm is proposed for the shortcomings of genetic algorithm to prematurely mature and fall into local optimal solution.In the selection operation,a combination of elite reservation and roulette is adopted,and a two-point crossover strategy is adopted in the cross operation,and the center pair is adopted in the mutation operation.Change the mutation strategy and add a local iteration operator after the mutation operation.An adaptive step size factor is proposed for the short-term convergence speed and the low convergence accuracy of the cuckoo algorithm,and the Levi flight change formula is redefined.Combined with the PSPLIB project library,the optimal parameters of the improved genetic algorithm after 1000 iteration number is:population size N=25;number of iterations 1=40;crossover probability Pc=0.8;mutation probability Pm=0.25.The optimal parameter combination of the adaptive cuckoo algorithm after 1000 iteration number is:population size N=15;iteration number I=67;step factor upper boundamax=0.9;step factor lower bound amin=0.01.The scheduling scheme is output under the optimal parameters and compared with various mainstream algorithms.The experimental results verify the problem of project scheduling with higher complexity and more iterations.The adaptive cuckoo algorithm has the more stable convergence curve and higher arithmetic accuracy.Introduce the example of multinational compressor assembly project,optimize the scheduling by using the better adaptive cuckoo algorithm,get the scheduling scheme with shorter construction period and balanced resource utilization,output the iteration graph,schedule,resource utilization figure and resource configuration Gantt chart.Focus on the impact of resource factors on the construction period,and compare the changes in resource demand and construction period under the condition of resource constraints.The project period is shortened by 32%without resource constraints,but the resource volume is increased by 120%.The orthogonal test was used to obtain the optimal resource level.At this level,the construction period was shortened by 21%,while the resource amount was only increased by 40%.Finally,through the analysis of variance,we find the resource factors that have significant impact on the construction period.The final result verifies the efficiency and practicability of the adaptive cuckoo algorithm in actual production scheduling projects.For the manufacturing project scheduling problem with high complexity and many iterations,the adaptive cuckoo algorithm has a more stable convergence curve and higher arithmetic precision in terms of algorithm performance.In terms of applicability,the adaptive cuckoo algorithm It is capable of outputting a scheduling scheme with balanced resources and shorter duration.