Job shop scheduling with beam search

Cataloged from PDF version of article.Beam Search is a heuristic method for solving optimization problems. It is an adaptation of the branch and bound method in which only some nodes are evaluated in the search tree. At any level, only the promising nodes are kept for further branching and remaining nodes are pruned o permanently. In this paper, we develop a beam search based scheduling algorithm for the job shop problem. Both the makespan and mean tardiness are used as the performance measures. The proposed algorithm is also compared with other well known search methods and dispatching rules for a wide variety of problems. The results indicate that the beam search technique is a very competitive and promising tool which deserves further research in the scheduling literature. Ó 1999 Elsevier Science B.V. All rights reserved

Operation-based flow-time estimation in dynamic job shops

Cataloged from PDF version of article.In the scheduling literature, estimation of job owtimes has been an important issue since the late 1960s. The previous studies focus on the problem in the context of due date assignment and develop methods using aggregate information in the estimation process. In this study, we propose a new owtime estimation method that utilizes the detailed job, shop and route information for operations of jobs as well as the machine imbalance information. This type of information is now available in computer-integrated manufacturing systems. The performance of the proposed method is measured by computer simulation under various experimental conditions. It is compared with the existing owtime estimation methods for a wide variety of performance measures. The results indicate that the proposed method outperforms all the other owtime estimation methods. Moreover, it is quite robust to changing shop conditions (i.e., machine breakdowns, arrival rate and processing time variations, etc.). A comprehensive bibliography is also provided in the paper. 2002 Elsevier Science Ltd. All rights reserved

Rescheduling frequency in an FMS with uncertain processing times and unreliable machines

Cataloged from PDF version of article.This paper studies the scheduling/rescheduling problem in a multi-resource FMS environment. Several reactive scheduling policies are proposed to address the effects of machine breakdowns and processing time variations. Both off-line and on-line scheduling methods are tested under a variety of experimental conditions. The performance of the system is measured for mean tardiness and makespan criteria. The relationships between scheduling frequency and other scheduling factors are investigated. The results indicated that a periodic response with an appropriate period length would be sufficient to cope with interruptions. It was also observed that machine breakdowns have more significant impact on the system performance than processing time variations. In addition, dispatching rules were found to be more robust to interruptions than the optimum-seeking off-line scheduling algorithm. A comprehensive bibliography is also included in the paper

Analysis of reactive scheduling problems in a job shop environment

Cataloged from PDF version of article.In this paper, we study the reactive scheduling problems in a stochastic manufacturing environment. Specifically, we test the several scheduling policies under machine breakdowns in a classical job shop system. In addition, we measure the e ect of system size and type of work allocation (uniform and bottleneck) on the system performance. The performance of the system is measured for the mean tardiness and makespan criteria. We also investigate a partial scheduling scheme under both deterministic and stochastic environments for several system configurations

A Neural Network Model for Scheduling Problems

Cataloged from PDF version of article.Artificial neural networks (ANNs) have been successfully applied to solve a variety of problems. This paper proposes a new neural network approach to solve the single machine mean tardiness scheduling problem and the minimum makespan job shop schedUling problem. The proposed network combines the characteristics of neural networks and algorithmic approaches. The performance of the network is compared with the existing scheduling algorithms under various experimental conditions. A comprehensive bibliography is also provided in the paper

Scheduling for non regular performance measure under the due window approach

Cataloged from PDF version of article.In the last two decades, Just-In-Time (JIT) production has proved to be an essential requirement of world class manufacturing. This has made schedulers most concerned about the realization of a JIT environment. The JIT concept requires not only a penalty for backorder and lateness but also for earliness. This can be translated into non-regular scheduling objectives. The most obvious objective can be to minimize the deviation of completion times. Concerning earliness/tardiness problems, researchers have usually considered systems where jobs incur no penalty for completion at a certain point of time (i.e. due date). In practice, however, job completions can also be accepted without penalty within an interval in time, which is known as the due window. This paper studies the scheduling problems in terms of the non-regular measure, mean absolute deviation (MAD), under the due window approach. The study is conducted in a dynamic job shop environment. Furthermore, we propose two new rules that perform quite e ectively for the MAD measure. 1999 Elsevier Science Ltd. All rights reserved

Analysis of order review/release problems in production systems

Cataloged from PDF version of article.Order Review/Release (ORR) activities have mostly been ignored in past job shop research. In most previous studies, arriving jobs are immediately released to the shop #oor without considering any information about the system or job characteristics. In practice however, these jobs are often "rst collected in a pool and then released to the system according to a speci"c criterion. Although practitioners often observe the bene"ts of ORR, researchers have found limited support for the use of these input reglation policies. One objective of this paper is to examine this research paradox in a capacitated system. We also o!er a new classi"cation framework for existing research work. Finally, for the "rst time in this paper, both periodic and continuous ORR methods are compared simultaneously under various experimental conditions against di!erent performance measures. The results of simulation experiments and statistical tests are also presented in the paper

Prevalence of dieting, overweight, body image satisfaction and associated psychological problems in adolescent boys

Purpose - The aim of the present study is to examine the severity of dieting and its association with obesity, body satisfaction and psychological problems in adolescent boys. Design/methodology/approach - A representative sample of 800 boys in the age group of 14-19 in Qatar was approached during the period from October to December, 2004 and 593 boys gave consent to participate in this study, thus giving a response rate of 74.1 per cent. Self-reports were obtained from 593 teenage boys using the adolescent dieting scale (ADS), and the self-reporting questionnaire (SRQ-20) for psychopathology. Findings - Of the studied subjects, 33.1 per cent were overweight, 10.1 per cent were extreme dieters and 37.4 per cent were intermediate dieters. Among the dieters, 34 per cent were overweight. Dieting was more likely in subjects who practiced exercise and who were perceived by peers or themselves as overweight. The extreme dieters experienced more psychological problems than the intermediate dieters and non-dieters. Extreme dieters reported sleeping problems (58.3 per cent), tired all the time (53.3 per cent) and felt like crying more than usual (50 per cent). Television was the main source of information on diet (61.7 per cent). Originality/value - The present study findings provide a strong evidence for the association between frequent dieting and overweight, body image dissatisfaction and psychological problems

Hybrid Petri-nets for Modeling and Performance Evaluation of Supply Chains

Cataloged from PDF version of article.Modelling and analysis of complex and co-ordinated supply chains is a crucial task due to its inherent complexity and uncertainty. Therefore, the current research direction is to devise an efficient modelling technique that maps the dynamics of a real life supply chain and assists industrial practitioners in evaluating and comparing their network with other competing networks. Here an effective modelling technique, the hybrid Petri-net, is proposed to efficiently handle the dynamic behaviour of the supply chain. This modelling methodology embeds two enticing features, i.e. cost and batch sizes, in deterministic and stochastic Petri-net for the modelling and performance evaluation of supply chain networks. The model is subsequently used for risk management to investigate the issues of supply chain vulnerability and risk that has become a major research subject in recent years. In the test bed, a simple productive supply chain and an industrial supply chain are modelled with fundamental inventory replenishment policy. Subsequently, its performance is evaluated along with the identification and assessment of risk factors using analytical and simulation techniques respectively. Thus, this paper presents a complete package for industrial practitioners to model, evaluate performance and manage risky events in a supply chain

Backtracking and exchange of information: Methods to enhance a beam search algorithm for assembly line scheduling

Cataloged from PDF version of article.Beam search (BS) is used as a heuristic to solve various combinatorial optimization problems, ranging from scheduling to assembly line balancing. In this paper, we develop a backtracking and an exchange-of-information (EOI) procedure to enhance the traditional beam search method. The backtracking enables us to return to previous solution states in the search process with the expectation of obtaining better solutions. The EOI is used to transfer information accumulated in a beam to other beams to yield improved solutions. We developed six different versions of enhanced beam algorithms to solve the mixed-model assembly line scheduling problem. The results of computational experiments indicate that the backtracking and EOI procedures that utilize problem specific information generally improve the solution quality of BS. 2007 Elsevier B.V. All rights reserved