Two Problems Of Batch Scheduling With Learning Effect

Scheduling is an important research field in combinatorial optimization.It is widely used in transports,computer science,industrial and other sectors.It has been a hottest topic in the research of combinatorial optimization.Since 1950's batch scheduling and scheduling with learning effect are relatively new scheduling models,which are attracting more and more attention recently.In this dissertation,some special batch schedulings are studied.The optimal algorithms of the problem are given.The structure of the article is arranged as follow:In chapter 1,some notations,definitions and basic background information about the subject are introduced,then,the introduction of our research have been summarized.In chapter2,the problems of scheduling with learning effect on identical parallel batch machines are considered.The objective is to minimize the total weighted completion times.Frist of all,we know the problem with identical parallel machine is NP-hard,so we discuss the special case where jobs have constant processing time.In this chapter,the optimal algorithms of the problem are given, and the computational complexity is analysiscd.In chapter 3,batch scheduling with learning effect is considered,the object is to minimize reward the ahead and punish the delay.We know that this problem is NP-hard,so wc discuss the special case where jobs have constant processing times,and analysis the computational complexity.