The single-machine scheduling problems with deteriorating jobs and learning effect

In this paper we consider a single-machine scheduling model with deteriorating jobs and simultaneous learning, and we introduce polynomial solutions for single machine makespan minimization, total flow times minimization and maximum lateness minimization corresponding to the first and second special cases of our model under some agreeable conditions. However, corresponding to the third special case of our model, we show that the optimal schedules may be different from those of the classical version for the above objective functions.

TWO SCHEDULING PROBLEMS IN GROUP TECHNOLOGY WITH DETERIORATING JOBS

This paper considers single-machine scheduling problems in group technology with the jobs' processing times being simple linear functions of their start times.The objective functions are the ~minimizing of makespan and total weighted completion time.Some optimal conditions and algorithms are given and the fact that the problem of total weighted completion times is NP-hard is proved.

A multiple-criterion model for machine scheduling with constant deteriorating jobs

We consider a scheduling problem involving a single processor utilized by two customers with constant deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. Traditionally, such scenarios are modeled by assuming that each customer has the same criterion. In practice, this assumption may not hold. Instead of using a single criterion, we examine the implications of minimizing an aggregate scheduling objective function in which jobs belonging to different customers are evaluated with their individual criteria. We examine three basic scheduling criteria： minimizing makespan, minimizing maximum lateness, and minimizing total weighted completion time. We demonstrate all the scheduling problems considered are polynomially solvable.

Scheduling deteriorating jobs with rejection on dominant machines

The permutation flow shop scheduling problems with deteriorating jobs and rejection on dominant machines were studied.The objectives are to minimize the makespan of scheduled jobs plus the total rejection penalty and the total completion time of scheduled jobs plus the total rejection penalty.For each objective, polynomial time algorithms based on dynamic programming were presented.

Minmax Common Due-Window Assignment Scheduling with Deteriorating Jobs

This paper investigates the common due-window assignment scheduling problem with deteriorating jobs on a single machine in which the processing time of a job is a proportional function of its starting time.The goal is to minimize the maximum value of earliness and tardiness penalties,as well as due-window location cost,and size cost.Depending on whether the location and size of due-window are known,this paper studies three relevant cases,all of which are solvable in polynomial time.

Batch Scheduling with Deteriorating Jobs to Minimize the Total Completion Time

We consider bounded parallel-batch scheduling with proportional-linear deteriorating jobs and the objective to minimize the total completion time.We give some properties of optimal schedules for the problem and present for it a dynamic programming algorithm running in O(b^(2)m^(2)2^(m))time,where b is the size of a batch and m is the number of distinct deterioration rates.

An approximation algorithm for parallel machine scheduling with simple linear deterioration

In this paper, a parallel machine scheduling problem was considered , where the processing time of a job is a simple linear function of its starting time. The objective is to minimize makespan. A fully polynomial time approximation scheme for the problem of scheduling n deteriorating jobs on two identical machines was worked out. Furthermore, the result was generalized to the case of a fixed number of machines.