On-line scheduling on a batch machine to minimize makespan with limited restarts

We study the on-line scheduling on an unbounded batch machine to minimize makespan. In this model, jobs arrive over time and batches are allowed limited restarts. Any batch that contains a job which has already been restarted once cannot be restarted any more. We provide a best possible on-line algorithm for the problem with a competitive ratio .     

同时最小化最大费用和最大完工时间的双代理无界平行分批排序

有两个代理A和B, 每个代理都各自有一个工件集. 同一个代理的工件可以在同一批中加工, 而且每一个代理都有一个需要最小化的函数. 研究在无界平行分批处理机上同时最小化代理A的最大费用和代理B的最大完工时间问题, 并给出一个算法, 它可在多项式时间内找到关于这个问题的所有Pareto最优点.     

An improved on-line algorithm for scheduling on two unrestrictive parallel batch processing machines

We consider the problem of on-line scheduling a set of n jobs on two parallel batch processing machines. The objective is to minimize the makespan. We provide an algorithm for the problem that is better than one given in the literature, improving the competitive ratio from to .     

On scheduling an unbounded batch machine

A batch machine is a machine that can process up to c jobs simultaneously as a batch, and the processing time of the batch is equal to the longest processing time of the jobs assigned to it. In this paper, we deal with the complexity of scheduling an unbounded batch machine, i.e., c=+∞. We prove that minimizing total tardiness is binary NP-hard, which has been an open problem in the literature. Also, we establish the pseudopolynomial solvability of the unbounded batch machine scheduling problem with job release dates and any regular objective. This is distinct from the bounded batch machine and the classical single machine scheduling problems, most of which with different release dates are unary NP-hard. Combined with the existing results, this paper provides a nearly complete mapping of the complexity of scheduling an unbounded batch machine.     

Batch scheduling of simple linear deteriorating jobs on a single machine to minimize makespan

We consider a scheduling problem in which n jobs are to be processed on a single machine. The jobs are processed in batches and the processing time of each job is a simple linear function of its waiting time, i.e., the time between the start of the processing of the batch to which the job belongs and the start of the processing of the job. The objective is to minimize the makespan, i.e., the completion time of the last job. We first show that the problem is strongly NP-hard. Then we show that, if the number of batches is B  , the problem remains strongly NP-hard when B?U$B?U$ for a variable U?2$U?2$ or B?U$B?U$ for any constant U?2$U?2$. For the case of B?U$B?U$, we present a dynamic programming algorithm that runs in pseudo-polynomial time and a fully polynomial time approximation scheme (FPTAS) for any constant U?2$U?2$. Furthermore, we provide an optimal linear time algorithm for the special case where the jobs are subject to a linear precedence constraint, which subsumes the case where all the job growth rates are equal.     

Mixed integer formulation to minimize makespan in a flow shop with batch processing machines

Batch processing machines are commonly used in wafer fabrication, kilns, and chambers used for environmental stress screening (ESS). This paper proposes two models to schedule batches of jobs on two machines in a flow shop. A set of jobs with known processing times and sizes has to be grouped, to form batches, in order to be processed on the batch processing machines. The jobs are nonidentical in size. The processing time of a batch is the longest processing time of all the jobs in that batch. Mixed integer formulations are proposed for the flow shop problem when the buffer capacity is unlimited or zero. Numerical examples are presented to demonstrate the application of our model.     

On-line scheduling to minimize average completion time revisited

We consider the scheduling problem of minimizing the average-weighted completion time on identical parallel machines when jobs are arriving over time. For both the preemptive and the nonpreemptive setting, we show that straightforward extensions of Smith's ratio rule yield smaller competitive ratios than the previously best-known deterministic on-line algorithms.     

Unbounded parallel batch scheduling with job delivery to minimize makespan

We consider unbounded parallel batch scheduling with job delivery to minimize makespan. When the jobs have identical size, we provide a polynomial-time algorithm. When the jobs have non-identical sizes, we provide a heuristic with a worst-case performance ratio 7/4.     

Optimal methods for batch processing problem with makespan and maximum lateness objectives

In this paper we consider the problem of scheduling n jobs on a single batch processing machine in which jobs are ordered by two customers. Jobs belonging to different customers are processed based on their individual criteria. The considered criteria are minimizing makespan and maximum lateness. A batching machine is able to process up to b jobs simultaneously. The processing time of each batch is equal to the longest processing time of jobs in the batch. This kind of batch processing is called parallel batch processing. Optimal methods for three cases are developed: unbounded batch capacity, b > n, with compatible job groups and bounded batch capacity, b  n, with compatible and non compatible job groups. Each job group represents a different class of customers and the concept of being compatible means that jobs which are ordered by different customers are allowed to be processed in a same batch. We propose an optimal method for the problem with incompatible groups and unbounded batches. About the case when groups are incompatible and bounded batches, our proposed method is considered as optimal when the group with maximum lateness objective has identical processing times. We regard this method, however, as a heuristic when these processing times are different. When groups are compatible and batches are bounded we consider another problem by assuming the same processing times for the group which has the maximum lateness objective and propose an optimal method for this problem.     

Batch delivery scheduling with batch delivery cost on a single machine

We consider a scheduling problem in which n independent and simultaneously available jobs are to be processed on a single machine. The jobs are delivered in batches and the delivery date of a batch equals the completion time of the last job in the batch. The delivery cost depends on the number of deliveries. The objective is to minimize the sum of the total weighted flow time and delivery cost. We first show that the problem is strongly NP-hard. Then we show that, if the number of batches is B, the problem remains strongly NP-hard when B ? U for a variable U ? 2 or B ? U for any constant U ? 2. For the case of B ? U, we present a dynamic programming algorithm that runs in pseudo-polynomial time for any constant U ? 2. Furthermore, optimal algorithms are provided for two special cases: (i) jobs have a linear precedence constraint, and (ii) jobs satisfy the agreeable ratio assumption, which is valid, for example, when all the weights or all the processing times are equal.     

A single machine batch scheduling problem with bounded batch size

We address a single-machine batch scheduling problem to minimize total flow time. Processing times are assumed to be identical for all jobs. Setup times are assumed to be identical for all batches. As in many practical situations, batch sizes may be bounded. In the first setting studied in this paper, all batch sizes cannot exceed a common upper bound. In the second setting, all batch sizes share a common lower bound. An optimal solution consists of the number of batches and their (integer) size. We introduce an efficient solution for both problems.     

ON-LINE PROBLEMS OF MINIMIZING MAKESPAN ON A SINGLE BATCH PROCESSING MACHINE WITH NONIDENTICAL JOB SIZES

The on-line problem of scheduling on a batch processing machine with nonidentical job sizes to minimize makespan is considered. The batch processing machine can process a number of jobs simultaneously as long as the total size of these jobs being processed does not exceed the machine capacity. The processing time of a batch is given by the longest processing time of any job in the batch. Each job becomes available at its arrival time, which is unknown in advance, and its processing time becomes known upon its arrival. The paper deals with two variants： the case only with two distinct arrival times and the general case. For the first case, an on-line algorithm with competitive ratio 119/44 is given. For the latter one, a simple algorithm with competitive ratio 3 is given. For both variants the better ratios can be obtained if the problem satisfies proportional assumption.     

Single machine batch scheduling to minimize the weighted number of late jobs

The single machine batch scheduling problem to minimize the weighted number of late jobs is studied. In this problem,n jobs have to be processed on a single machine. Each job has a processing time, a due date and a weight. Jobs may be combined to form batches containing contiguously scheduled jobs. For each batch, a constant set-up time is needed before the first job of this batch is processed. The completion time of each job in the batch coincides with the completion time of the last job in this batch. A job is late if it is completed after its due date. A schedule specifies the sequence of jobs and the size of each batch, i.e. the number of jobs it contains. The objective is to find a schedule which minimizes the weighted number of late jobs. This problem isNP-hard even if all due dates are equal. For the general case, we present a dynamic programming algorithm which solves the problem with equal weights inO(n ³) time. We formulate a certain scaled problem and show that our dynamic programming algorithm applied to this scaled problem provides a fully polynomial approximation scheme for the original problem. Each algorithm of this scheme has a time requirement ofO(n ³/ +n ³ logn). A side result is anO(n logn) algorithm for the problem of minimizing the maximum weight of late jobs.Supported by INTAS Project 93-257.     

List scheduling algorithms to minimize the makespan on identical parallel machines

In this paper we present constructive algorithms for the classical deterministic scheduling problem of minimizing the makespan on identical machines. Since the problem is known to beNP-hard in the strong sense, the approximate algorithms play a relevant role when solving this problem. The proposed algorithms are based on list scheduling procedures, but the assignment rule is not the same for the full set of jobs. Computational results show that these algorithms perform very well. This research has been partially supported by the Research Project H015/2000, Universidad de Alcalá. The authors are indebted to Joaquín Pérez and the referees for their helpful remarks and comments. We also wish to thank Paul Alexander Ayres for his help in the correct use of English.     

Single machine scheduling with general job-dependent aging effect and maintenance activities to minimize makespan

This paper considers single machine scheduling with an aging effect in which the processing time of a job depends on its position in a sequence. It is assumed that aging ratios are job-dependent and machine can be maintained some times in a schedule. After a maintenance activity, machine will be restored to its initial condition. The processing of jobs and the maintenance activities of machine are scheduled simultaneously. The objective is to schedule the jobs and the maintenance activities, so as to minimize the makespan. We provide a polynomial time algorithm to solve the problem.     

Preemptive scheduling of jobs with agreeable due dates on a single machine to minimize total tardiness

We consider the problem of scheduling n preemptive jobs on a single machine to minimize total tardiness, subject to agreeable due dates, i.e., a later release date corresponds to a later due date. We prove that the problem is -hard in the ordinary sense by showing that it is -hard, and deriving a pseudo-polynomial algorithm for it.