Research On Cloud Job Shop Scheduling Algorithms Considering Multi-cost Indicators

The workshop scheduling in the cloud manufacturing environment has the characteristics of rich scheduling resources,high degree of product personalization,complex product structure,and diversified product processing processes.Therefore,in the cloud manufacturing environment,how to rationally utilize the workshop scheduling resources and effectively manage the processing processes,so as to shorten the processing cycle and reduce the processing cost of products,has become a research hotspot in the field of cloud manufacturing technology.If we ensure that the product processing cycle is shortened,only the load balancing of the shop scheduling resources is pursued,but the cost index of the process processing consumption is neglected,which is not in line with the cloud manufacturing concept.This paper designs a cloud shop scheduling algorithm that considers the energy cost index.The scheduling algorithm targets the energy consumption cost and processing time,and solves the cloud workshop scheduling problem according to the process characteristics of the product processing and the scheduling resources of the shop.In the cloud manufacturing environment,different companies have different goals for product processing in different periods.In addition to the processing cycle and energy cost indicators,there are still indicators and scenarios that have not been considered,such as coordinating consideratio n of time cost and energy cost and transportation costs,etc.In this paper,a cloud shop scheduling algorithm considering multi-cost constraints is designed.The three constraints of time cost,energy cost and transportation cost are targeted,and the three constraint weights are integrated and adjusted.According to the characteristics of cloud shop scheduling,the genetic algorithm is used to solve the shop scheduling problem.The example shows that the algorithm takes into account the weight requirements of each index in solving the mult i-cost index constrained cloud job shop scheduling problem,and has certain scalability.Considering whether it is an ant colony algorithm or a genetic algorithm,even if there is improvement in the auxiliary strategy,the defects of the two algorithms in solving the shop scheduling problem cannot be avoided.This paper also designs a mult i-cost constrained cloud job shop scheduling algorithm based on fus ion algorithm,which integrates ant colony algorithm and genetic algorithm.Firstly,the genetic algorithm is used to solve the fuzzy result of the cloud shop sched uling problem.Then the result is used as input,and the ant colony algorithm is used to obtain the exact solution of the problem.The algorithm not only retains the advantages of the two algorithm design and the effect of the auxiliary strategy,but also avoids the shortcomings of the two algorithms independently solving the scheduling problem,and can effective ly solve the multi-cost constrained cloud shop scheduling problem.