A tardiness-concerned constructive method for the identical parallel machine scheduling

Xi, Yue; Jang, Jin Seok; Friedman, Douglas C.; Hou, Wanrong

doi:10.1007/s00170-015-6834-7

Cited by 4 publications

(10 citation statements)

References 46 publications

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“…Constraint (10) indicates that each machine can process only one job at any time. Constraint (11) gives the range of variables. Constraint (12) defines the maximum completion time.…”

Section: The Maximum Completion Time Of All Jobs;mentioning

confidence: 99%

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Parallel machine scheduling with dynamic resource allocation via a master–slave genetic algorithm

Tian

et al. 2018

IEEJ Transactions Elec Engng

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Scheduling problems with resource allocation have become of increasing interest in the academic and industrial areas in recent years. This study investigates parallel machine scheduling with dynamic resource allocation under the objective of minimizing the makespan, where the processing of jobs needs an additional resource that can be assigned and reassigned among all jobs, and the processing time of jobs is a function of the amount of allocated resources. Four decisions must be made in a schedule, namely job assignment, job sequence, resource allocation and jobs' starting time. In order to solve it efficiently, a master-slave genetic algorithm is proposed to determine the decisions of job assignment, job sequence and resource allocation, and a greedy heuristic rule is designed to determine the jobs' starting time. To examine the performance of the proposed algorithm, simulation experiments are carried out on a set of instances, and similar existing algorithms and the standard genetic algorithm are chosen as for comparison. The experimental results show that the proposed algorithm is a promising optimizer in solving the investigated problem.

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“…Constraint (10) indicates that each machine can process only one job at any time. Constraint (11) gives the range of variables. Constraint (12) defines the maximum completion time.…”

Section: The Maximum Completion Time Of All Jobs;mentioning

confidence: 99%

“…In recent years, the studies on parallel machine scheduling have received much interest [9][10][11][12]. In real-world manufacturing or service systems, a job may need different kinds of resources to be processed, e.g., human, water, and electricity.…”

Section: Introductionmentioning

confidence: 99%

Parallel machine scheduling with dynamic resource allocation via a master–slave genetic algorithm

Tian

et al. 2018

IEEJ Transactions Elec Engng

View full text Add to dashboard Cite

show abstract

“…if a given job h is processed on a given machine j , a predecessor i must exist on the same machine. Constraint (10) indicates that each machine can process only one job at a time. Constraint (11) offers the range of variables.…”

Section: Problem Statementmentioning

confidence: 99%

“…Each job has three processing modes, and the amount of resources in all the three processing modes is set to 1, 2, 3, respectively. The processing time of all jobs in the first mode p i 1 is generated from a uniform distribution U [10,50], and the processing time in the second and third modes is calculated as in (15), where α is a coefficient that is set to 0.6. Based on this method, 28 test instances are generated in total.…”

Section: Test Instance Generationmentioning

confidence: 99%

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Job scheduling and resource allocation in parallel‐machine system via a hybrid nested partition method

Jiang

Tian

et al. 2018

IEEJ Transactions Elec Engng

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Scheduling problems with resource allocation have received much attention in the academic and industrial communities in recent years. This study addresses a parallel-machine scheduling problem with resource allocation under the objective of minimizing the makespan, where jobs need an additional resource that is allocated to machines in advance. The processing time of jobs is a function of the amount of allocated resources on their corresponding machines. In order to deal with this problem, three decisions must be made, i.e. resource allocation among machines, job assignment on machines, and job sequence on each machine. To solve this problem efficiently, a constructive heuristic approach and a hybrid nested partition method are designed to make these three decisions. Simulation experiments are carried out on a set of instances, and two existing algorithms are chosen to be compared with the proposed algorithms. Experimental results show that the proposed algorithms are promising in coping with this problem.

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A unified heuristic and an annotated bibliography for a large class of earliness–tardiness scheduling problems

Kramer

Subramanian

2017

J Sched

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This work proposes a unified heuristic algorithm for a large class of earliness-tardiness (E-T) scheduling problems. We consider single/parallel machine E-T problems that may or may not consider some additional features such as idle time, setup times and release dates. In addition, we also consider those problems whose objective is to minimize either the total (average) weighted completion time or the total (average) weighted flow time, which arise as particular cases when the due dates of all jobs are either set to zero or to their associated release dates, respectively. The developed local search based metaheuristic framework is quite simple, but at the same time relies on sophisticated procedures for efficiently performing local search according to the characteristics of the problem. We present efficient move evaluation approaches for some parallel machine problems that generalize the existing ones for single machine problems. The algorithm was tested in hundreds of instances of several E-T problems and particular cases. The results obtained show that our unified heuristic is capable of producing high quality solutions when compared to the best ones available in the literature that were obtained by specific methods. Moreover, we provide an extensive annotated bibliography on the problems related to those considered in this work, where we not only indicate the approach(es) used in each publication, but we also point out the characteristics of the problem(s) considered. Beyond that, we classify the existing methods in different categories so as to have a better idea of the popularity of each type of solution procedure.

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A tardiness-concerned constructive method for the identical parallel machine scheduling

Cited by 4 publications

References 46 publications

Parallel machine scheduling with dynamic resource allocation via a master–slave genetic algorithm

Parallel machine scheduling with dynamic resource allocation via a master–slave genetic algorithm

Job scheduling and resource allocation in parallel‐machine system via a hybrid nested partition method

A unified heuristic and an annotated bibliography for a large class of earliness–tardiness scheduling problems

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