Parallel machine scheduling with maintenance activities

Yoo, Jaewook; Lee, Ik Sun

doi:10.1016/j.cie.2016.09.020

Cited by 48 publications

(19 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Dehua Xu and Yang [26] presented a computational programming model for two parallel scheduling machines where one machine is often unavailable, jobs are non-preemptive. Yoo and Lee [54] considered a problem of scheduling on parallel machines where each machine needs maintenance once over a given time period. The study's objective is to find a coordinated schedule for jobs and maintenance tasks to reduce the scheduling costs measured by either one of several objective measures, such as makespan.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

et al. 2021

View full text Add to dashboard Cite

In this study, the objective of minimizing makespan has been considered for a scheduling problem of identical parallel machines with a single server and unavailability constraints. The unavailability constraints correspond to preventive maintenance periods. In this study, the jobs and the maintenance periods are scheduled simultaneously. This scheduling problem has a wide range of potential application areas in the manufacturing environment. In addition, the studied problem is a challenging one from theoretical point of view, due to its NP-Hardness. To conduct the study, a lower bound (LB) for the problem, and three metaheuristics namely Simulated Annealing (SA), Tabu Search (TS), and Genetic Algorithm (GA) have been proposed. The best parameters settings of the proposed algorithms were conducted using pilot runs with a Taguchi design. The algorithms performance has been assessed by using a set of test problems generated randomly. These test problems are based on a literature benchmark. The size of the instances, or number of jobs, were up to 500. Along with the performance analysis of the proposed algorithms, the effect of varying processing times and unavailability periods on the performance of the proposed algorithms is studied. The present work provides strong evidence of the efficiency and the performance of the proposed algorithms.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Perawatan kendaraan merupakan suatu kegiatan yang terencana untuk mencegah terjadinya kesalahan potensial yang mengakibatkan kerusakan. Perhatikan bahwa biaya pemeliharaan mencakup persentase besar dari total biaya operasional, sehingga sangat wajar untuk memasukkan kegiatan pemeliharaan dalam jadwal (Yoo & Lee, 2016;Gustavsson, Patriksson, Strömberg, Wojciechowski, & Önnheim, 2014). Dalam jadwal perawatan kendaraan yang dilakukan secara berkala pada setiap kendaraan sangatlah berbeda-beda penanganannya, dilihat dari segi merk, type/jenis kendaraan, serta jarak tempuh pada kendaraan itu sendiri.…”

Section: Pendahuluanunclassified

Penerapan Algoritma K-Means Clustering Pada K-Harmonic Means Untuk Schedule Preventive Maintenance Service

2014

Jurnal Sisfo Unsurya

View full text Add to dashboard Cite

Vehicle maintenance is a very important sector in terms of economy and safety, a good understanding of vehicle maintenance is very important from the owner of the vehicle it self or from the company. Maintenance for the vehicle is considered as part structure of the activity in a series of improvements, as well as a planned activity to prevent potential errors resulting in damage. Schedule preventive maintenance is one of the methods that are used for vehicle maintenance scheduling. SPM is widely used because it can determine component reliability item, so as to reduce the cost of repairs, but this method has the disadvantage that reparations are made to the unit item could potentially breakdown, as well as the application of SPM only on certain types of vehicles. To solve this problem it is proposed the one application of a method, algorithm K-Means Clustering is one of the methods to be applied in the schedule vehicle maintenance services, K-Means algorithm is widely used because it is easy and simple. From the models created will then be tested using Confucion Matrix to determine how the level of accuracy, and describes the results of a positive predictive accuracy results are correct, the positive predictions were wrong, negative predictions are true, and false negative predictions. From these experiments showed that the application of K-Means Clustering algorithms in the vehicle's maintenance schedule capable of generating predictive value and accuracy that is optimal by 70%.

show abstract

“…Preventive maintenance (PM) is one of the factors causing machines to be unavailable for processing jobs, and it can significantly affect the performance of job scheduling. e majority of the studies in the literature assumed that each maintenance activity is either assigned in advance, i.e., its starting and completion times are known, [4][5][6][7][8][9][10][11][12][13][14][15][16] or maintenance activities and jobs are jointly scheduled in the planning horizon [12,[17][18][19][20][21][22][23][24][25][26]. In the abovementioned studies, they assumed that the maintenance time (maintenance duration) is a constant; however, in some maintenance activities such as cleaning, refilling, and recharging, the maintenance time is a nondecreasing function of its starting time, i.e., the later the maintenance activity begins, the longer its duration.…”

Section: Introductionmentioning

confidence: 99%

Improved Approaches to Minimize the Makespan on Single-Machine Scheduling with Periodic Preventive Maintenance Activities

Zhou

Tsai

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

This paper addresses a single-machine scheduling problem with periodic preventive maintenance activities that are predeterministic so that the machine is not available all the time, and jobs have to be processed between two consecutive maintenance periods. We propose a mixed integer programming (MIP) model and two heuristics to minimize the makespan. With more constraints in our model, the model is more efficient than the recent model of Perez-Gonzalez and Framinan , and our model could solve problems with up to fifty jobs. Two heuristic algorithms, namely, H (MW) and H (LB∗), are also proposed, in which two bin-packing policies of the minimum waste and minimum lower bound are used, respectively. Furthermore, we also proposed an improvement procedure. The results showed that the heuristic H (MW) outperformed other heuristics of the paper, indicating that the bin-packing policy of the minimum waste is more effective than well-known ones such as full batch and best fit. Additionally, all the heuristic algorithms addressed in this paper combined with the improvement procedure could achieve a similar and high quality of solutions with a very tiny increase in computational expense.

show abstract

Parallel machine scheduling with maintenance activities

Cited by 48 publications

References 23 publications

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

Integrated Scheduling of Tasks and Preventive Maintenance Periods in a Parallel Machine Environment With Single Robot Server

Penerapan Algoritma K-Means Clustering Pada K-Harmonic Means Untuk Schedule Preventive Maintenance Service

Improved Approaches to Minimize the Makespan on Single-Machine Scheduling with Periodic Preventive Maintenance Activities

Contact Info

Product

Resources

About