Problèmes d'ordonnancement sur des machines parallèles avec des périodes de maintenance et un effet de détérioration : Minimisation de la charge totale des machines

National audienceLa planification de périodes d'indisponibilité, souvent considérées comme des périodes de maintenance, est très importante et vise à améliorer l'efficacité de l'entreprise en termes de coûts de production et de délais de livraison. Par exemple dans (Singh et Arvinderjit, 2013), la planification de maintenances permet de réduire les temps d'arrêt de 13,64% et d'augmenter les bénéfices de l'entreprise. Cependant les problèmes classiques d'ordonnancement considèrent que les machines sont toujours disponibles. Or cette hypothèse n'est pas toujours vraie. Depuis le début des années 1990, plusieurs travaux ont été menés sur l'ordonnancement en présence de périodes d'indisponibilité. La plupart de ces travaux considère que la durée de ces périodes est fixe. L'étude de l'ordonnancement simultané de tâches et de maintenances de durée variable a été initiée par Kubzin et Strusevich en 2005. En effet, dans certains secteurs d'activité, plus la période séparant deux maintenances est importante plus la maintenance à réaliser est lourde et donc plus sa durée est importante. D'autre part, l'état de la machine peut affecter les performances de la production. Ces variations sont généralement modélisées par un effet de détérioration ou un effet d'apprentissage.Dans l'ordonnancement avec un effet de détérioration, introduit initialement par Browne et Yechiali (1990), plus la date d'exécution d'une tâche est tardive plus la durée d'exécution est importante. Cette durée est expliquée par le vieillissement de la machine. D'où l'importance des périodes de maintenance pour contrer la détérioration de la machine et pour rétablir les conditions initiales de la machine. Dans la littérature, la détérioration de la machine est exprimée par plusieurs fonctions analytiques.Nous considérons dans ce travail que durant la période de fonctionnement les machines suivent un effet de détérioration. Les activités de maintenance permettent de contrer l'effet de détérioration, d'éviter les pannes et de rétablir les conditions initiales de la machine. Dans ce papier, nous nous intéressons aux problèmes d'ordonnancement sur des machines parallèles en présence d'un effet de détérioration et de maintenances de durée variable, dont le but est de minimiser la charge totale des machines

Pengaruh Learning EffectBergantung-Waktu dan Deteriorasi terhadap Penjadwalan Mesin Tunggal

Learning effect and deterioration do not fragmentary happen all the time. If both of them simultaneously found, the processing time of the job will increase yet decrease from the plan at once. The actual processing time of jobs are defined by function of their starting times and positions in the sequence. The effect of learning and deterioration on single machine scheduling at this paper is applied at a paper-mill. Learning effect as a result of regular performance-evaluation at this paper-mill reduce the effect of deterioration up to 206,5509 hours. Routing jobs by Earlier Due Date (EDD) rule construct the optimal result under maximum lateness case in this paper than either Most Urgent Job (MUJ) or Shortest Processing Time (SPT) do. The maximum lateness under EDD rule is 13,6% less than sequence that is recently used in that paper-mill

Due-date assignment and parallel-machine scheduling with deteriorating jobs

Author name used in this publication: T. C. E. ChengAuthor name used in this publication: L. Y. KangAuthor name used in this publication: C. T. Ng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Un ordonnancement dynamique de tâches stochastiques sur un seul processeur

We show that a particular dynamic priority given to jobs in a multitasks operating system of computers is a deteriorating jobs or a delaying jobs scheduling. Under some assumptions we also show that it is an index rule. To do this, we present the tool of bandit processes to solve stochastic scheduling problems on a single machine

Single-machine scheduling with deteriorating jobs under a series-parallel graph constraint

Author name used in this publication: C. T. NgAuthor name used in this publication: T. C. E. Cheng2007-2008 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Simple assembly line balancing problem under task deterioration

This paper introduces the effect of task deterioration in simple assembly line balancing problem. In many realistic assembly lines, a deterioration task is considered when a task is started earlier than the assigned time since the station time is constant and the earliness of the task does not reduce the cycle time. This phenomenon is known as deteriorating tasks. Therefore, we seek an optimal assignment and schedule of tasks in workstations, in order to minimize the number of stations for a given cycle time, which is known as SALBP-1. For this purpose, a mathematical model is proposed. Since the pure SALBP-1 is proved to be NP-hard and considering task deterioration complicates problem further, we propose a genetic algorithm for solving such problem. Several well-known test problems are solved to study the performance of the proposed approach

Parallel-Machine Scheduling Problems with Past-Sequence-Dependent Delivery Times and Aging Maintenance

We consider parallel-machine scheduling problems with past-sequence-dependent (psd) delivery times and aging maintenance. The delivery time is proportional to the waiting time in the system. Each machine has an aging maintenance activity. We develop polynomial algorithms to three versions of the problem to minimize the total absolute deviation of job completion times, the total load, and the total completion time

A new mathematical model for single machine batch scheduling problem for minimizing maximum lateness with deteriorating jobs

This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model