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.     

Single-machine scheduling with deteriorating jobs and learning effects to minimize the makespan

This paper studies the single-machine scheduling problem with deteriorating jobs and learning considerations. The objective is to minimize the makespan. We first show that the schedule produced by the largest growth rate rule is unbounded for our model, although it is an optimal solution for the scheduling problem with deteriorating jobs and no learning. We then consider three special cases of the problem, each corresponding to a specific practical scheduling scenario. Based on the derived optimal properties, we develop an optimal algorithm for each of these cases. Finally, we consider a relaxed model of the second special case, and present a heuristic and analyze its worst-case performance bound.     

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 .     

Parallel-machine scheduling with simple linear deterioration to minimize total completion time

We consider the parallel-machine scheduling problem in which the processing time of a job is a simple linear increasing function of its starting time. The objective is to minimize the total completion time. We give a fully polynomial-time approximation scheme (FPTAS) for the case with m identical machines, where m is fixed. This study solves an open problem that has been posed in the literature for ten years.     

On-line scheduling on a batch processing machine with unbounded batch size to minimize the makespan

We present on-line algorithms to minimize the makespan on a single batch processing machine. We consider a parallel batching machine that can process up to b jobs simultaneously. Jobs in the same batch complete at the same time. Such a model of a batch processing machine has been motivated by burn-in ovens in final testing stage of semiconductor manufacturing. We deal with the on-line scheduling problem when jobs arrive over time. We consider a set of independent jobs. Their number is not known in advance. Each job is available at its release date and its processing requirement is not known in advance. This general problem with infinite machine capacity is noted 1∣p − batch, r_j, b = ∞∣C_max. Deterministic algorithms that do not insert idle-times in the schedule cannot be better than 2-competitive and a simple rule based on LPT achieved this bound [Z. Liu, W. Yu, Scheduling one batch processor subject to job release dates, Discrete Applied Mathematics 105 (2000) 129–136]. If we are allowed to postpone start of jobs, the performance guarantee can be improved to 1.618. We provide a simpler proof of this best known lower bound for bounded and unbounded batch sizes. We then present deterministic algorithms that are best possible for the problem with unbounded batch size (i.e., b = ∞) and agreeable processing times (i.e., there cannot exist an on-line algorithm with a better performance guarantee). We then propose another algorithm that leads to a best possible algorithm for the general problem with unbounded batch size. This algorithm improves the best known on-line algorithm (i.e. [G. Zhang, X. Cai, C.K. Wong, On-line algorithms for minimizing makespan on batch processing machines, Naval Research Logistics 48 (2001) 241–258]) in the sense that it produces a shortest makespan while ensuring the same worst-case performance guarantee.     

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.     

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.     

Minimizing makespan for a bipartite graph on a single processor with an integer precedence delay

We consider the makespan minimization for a unit execution time task sequencing problem with a bipartite precedence delays graph and a positive precedence delay d. We prove that the associated decision problem is strongly NP-complete and we provide a non-trivial polynomial sub-case. We also give an approximation algorithm with ratio .     

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.     

Parallel machines scheduling to minimize job tardiness and machine deteriorating cost with deteriorating jobs

This paper studies the parallel machines bi-criteria scheduling problem (PMBSP) in a deteriorating system. Sequencing and scheduling problems (SSP) have seldom considered the two phenomena concurrently. This paper discusses the parallel machines scheduling problem with the effects of machine and job deterioration. By the machine deterioration effect, we mean that each machine deteriorates at a different rate. This deterioration is considered in terms of cost which depends on the production rate, the machine’s operating characteristics and the kind of work done by each machine. Moreover, job processing times are increasing functions of their starting times and follow a simple linear deterioration. The objective functions are minimizing total tardiness and machine deteriorating cost. The problem of total tardiness on identical parallel machines is NP-hard, thus the problem with machine deteriorating cost as an additional term is also NP-hard. We propose the LP-metric method to show the importance of our proposed multi-objective problem. A metaheuristic algorithm is developed to locate optimal or near optimal solutions based on a Tabu search mechanism. Numerical examples are presented to show the efficiency of this model.     

Minimizing makespan on a single batching machine with release times and non-identical job sizes

We consider the problem of scheduling jobs with release times and non-identical job sizes on a single batching machine; our objective is to minimize makespan. We present an approximation algorithm with worst-case ratio 2+ε, where ε>0 can be made arbitrarily small.     

Scheduling linear deteriorating jobs with rejection on a single machine

We consider several single machine scheduling problems in which the processing time of a job is a linear function of its starting time and jobs can be rejected by paying penalties. The objectives are to minimize the makespan, the total weighted completion time and the maximum lateness/tardiness plus the total penalty of the rejected jobs. We show that these problems are NP-hard, and design algorithms based on dynamic programming (including pseudo-polynomial time optimal algorithms and fully polynomial time approximation schemes) to solve them.     

Scheduling of nonresumable jobs and flexible maintenance activities on a single machine to minimize makespan

This study addresses a single machine scheduling problem with periodic maintenance, where the machine is assumed to be stopped periodically for maintenance for a constant time w during the scheduling period. Meanwhile, the maintenance period [u, v] is assumed to have been previously arranged and the time w is assumed not to exceed the available maintenance period [u, v] (i.e. w ? v − u). The time u(v) is the earliest (latest) time at which the machine starts (stops) its maintenance. The objective is to minimize the makespan. Two mixed binary integer programming (BIP) models are provided for deriving the optimal solution. Additionally, an efficient heuristic is proposed for finding the near-optimal solution for large-sized problems. Finally, computational results are provided to demonstrate the efficiency of the models and the effectiveness of the heuristics. The mixed BIP model can optimally solve up to 100-job instances, while the average percentage error of the heuristic is below 1%.     

Complexity of single machine scheduling subject to nonnegative inventory constraints

This paper focuses on single machine scheduling subject to inventory constraints. Jobs either add items to an inventory or remove items from that inventory. Jobs that have to remove items cannot be processed if the required number of items is not available. We consider scheduling problems on a single machine with the minimization of the total weighted completion time, the maximum lateness, and the number of tardy jobs, respectively, as objective and determine their computational complexity. Since the general versions of our problems turn out to be strongly NP-hard, we consider special cases by assuming that different jobs have certain parameter values in common. We determine the computational complexity for all special cases when the objective is either to minimize total completion time or to minimize maximum lateness and for several special cases when the objective is either to minimize total weighted completion time or to minimize the number of tardy jobs.     

Scheduling jobs with release times preemptively on a single machine to minimize the number of late jobs

We give a direct combinatorial O(n³logn) algorithm for minimizing the number of late jobs on a single machine when jobs have release times and preemptions are allowed. Our algorithm improves the earlier O(n⁵) and O(n⁴) dynamic programming algorithms for this problem.