987 resultados para Scheduling models


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We address the problem of jointly determining shipment planning and scheduling decisions with the presence of multiple shipment modes. We consider long lead time, less expensive sea shipment mode, and short lead time but expensive air shipment modes. Existing research on multiple shipment modes largely address the short term scheduling decisions only. Motivated by an industrial problem where planning decisions are independent of the scheduling decisions, we investigate the benefits of integrating the two sets of decisions. We develop sequence of mathematical models to address the planning and scheduling decisions. Preliminary computational results indicate improved performance of the integrated approach over some of the existing policies used in real-life situations.

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Graphical tracking is a technique for crop scheduling where the actual plant state is plotted against an ideal target curve which encapsulates all crop and environmental characteristics. Management decisions are made on the basis of the position of the actual crop against the ideal position. Due to the simplicity of the approach it is possible for graphical tracks to be developed on site without the requirement for controlled experimentation. Growth models and graphical tracks are discussed, and an implementation of the Richards curve for graphical tracking described. In many cases, the more intuitively desirable growth models perform sub-optimally due to problems with the specification of starting conditions, environmental factors outside the scope of the original model and the introduction of new cultivars. Accurate specification for a biological model requires detailed and usually costly study, and as such is not adaptable to a changing cultivar range and changing cultivation techniques. Fitting of a new graphical track for a new cultivar can be conducted on site and improved over subsequent seasons. Graphical tracking emphasises the current position relative to the objective, and as such does not require the time consuming or system specific input of an environmental history, although it does require detailed crop measurement. The approach is flexible and could be applied to a variety of specification metrics, with digital imaging providing a route for added value. For decision making regarding crop manipulation from the observed current state, there is a role for simple predictive modelling over the short term to indicate the short term consequences of crop manipulation.

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This paper describes the development and solution of binary integer formulations for production scheduling problems in market-driven foundries. This industrial sector is comprised of small and mid-sized companies with little or no automation, working with diversified production, involving several different metal alloy specifications in small tailor-made product lots. The characteristics and constraints involved in a typical production environment at these industries challenge the formulation of mathematical programming models that can be computationally solved when considering real applications. However, despite the interest on the part of these industries in counting on effective methods for production scheduling, there are few studies available on the subject. The computational tests prove the robustness and feasibility of proposed models in situations analogous to those found in production scheduling at the analyzed industrial sector. (C) 2010 Elsevier Ltd. All rights reserved.

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This chapter studies a two-level production planning problem where, on each level, a lot sizing and scheduling problem with parallel machines, capacity constraints and sequence-dependent setup costs and times must be solved. The problem can be found in soft drink companies where the production process involves two interdependent levels with decisions concerning raw material storage and soft drink bottling. Models and solution approaches proposed so far are surveyed and conceptually compared. Two different approaches have been selected to perform a series of computational comparisons: an evolutionary technique comprising a genetic algorithm and its memetic version, and a decomposition and relaxation approach. © 2008 Springer-Verlag Berlin Heidelberg.

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In this paper, we propose three novel mathematical models for the two-stage lot-sizing and scheduling problems present in many process industries. The problem shares a continuous or quasi-continuous production feature upstream and a discrete manufacturing feature downstream, which must be synchronized. Different time-based scale representations are discussed. The first formulation encompasses a discrete-time representation. The second one is a hybrid continuous-discrete model. The last formulation is based on a continuous-time model representation. Computational tests with state-of-the-art MIP solver show that the discrete-time representation provides better feasible solutions in short running time. On the other hand, the hybrid model achieves better solutions for longer computational times and was able to prove optimality more often. The continuous-type model is the most flexible of the three for incorporating additional operational requirements, at a cost of having the worst computational performance. Journal of the Operational Research Society (2012) 63, 1613-1630. doi:10.1057/jors.2011.159 published online 7 March 2012

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This thesis deals with an investigation of combinatorial and robust optimisation models to solve railway problems. Railway applications represent a challenging area for operations research. In fact, most problems in this context can be modelled as combinatorial optimisation problems, in which the number of feasible solutions is finite. Yet, despite the astonishing success in the field of combinatorial optimisation, the current state of algorithmic research faces severe difficulties with highly-complex and data-intensive applications such as those dealing with optimisation issues in large-scale transportation networks. One of the main issues concerns imperfect information. The idea of Robust Optimisation, as a way to represent and handle mathematically systems with not precisely known data, dates back to 1970s. Unfortunately, none of those techniques proved to be successfully applicable in one of the most complex and largest in scale (transportation) settings: that of railway systems. Railway optimisation deals with planning and scheduling problems over several time horizons. Disturbances are inevitable and severely affect the planning process. Here we focus on two compelling aspects of planning: robust planning and online (real-time) planning.

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Crew scheduling and crew rostering are similar and related problems which can be solved by similar procedures. So far, the existing solution methods usually create a model for each one of these problems (scheduling and rostering), and when they are solved together in some cases an interaction between models is considered in order to obtain a better solution. A single set covering model to solve simultaneously both problems is presented here, where the total quantity of drivers needed is directly considered and optimized. This integration allows to optimize all of the depots at the same time, while traditional approaches needed to work depot by depot, and also it allows to see and manage the relationship between scheduling and rostering, which was known in some degree but usually not easy to quantify as this model permits. Recent research in the area of crew scheduling and rostering has stated that one of the current challenges to be achieved is to determine a schedule where crew fatigue, which depends mainly on the quality of the rosters created, is reduced. In this approach rosters are constructed in such way that stable working hours are used in every week of work, and a change to a different shift is done only using free days in between to make easier the adaptation to the new working hours. Computational results for real-world-based instances are presented. Instances are geographically diverse to test the performance of the procedures and the model in different scenarios.

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Zahnverlust zu Lebzeiten („antemortem tooth loss“, AMTL) kann als Folge von Zahnerkrankungen, Traumata, Zahnextraktionen oder extremer kontinuierlicher Eruption sowie als Begleiterscheinung fortgeschrittener Stadien von Skorbut oder Lepra auftreten. Nach dem Zahnverlust setzt die Wundheilung als Sekundärheilung ein, während der sich die Alveole mit Blut füllt und sich ein Koagulum bildet. Anschließend erfolgt dessen Umwandlung in Knochengewebe und schließlich verstreicht die Alveole derart, dass sie makroskopisch nicht mehr erkannt werden kann. Der Zeitrahmen der knöchernen Konsolidierung des Kieferkammes ist im Detail wenig erforscht. Aufgrund des gehäuften Auftretens von AMTL in menschlichen Populationen, ist die Erarbeitung eines Zeitfensters, mit dessen Hilfe durch makroskopische Beobachtung des Knochens die Zeitspanne seit dem Zahnverlust („time since tooth loss“, TSL) ermittelt werden kann, insbesondere im archäologischen Kontext äußerst wertvoll. Solch ein Zeitschema mit Angaben über die Variabilität der zeitlichen Abläufe bei den Heilungsvorgängen kann nicht nur in der Osteologie, sondern auch in der Forensik, der allgemeinen Zahnheilkunde und der Implantologie nutzbringend angewandt werden. rnrnNach dem Verlust eines Zahnes wird das Zahnfach in der Regel durch ein Koagulum aufgefüllt. Das sich bildende Gewebe wird rasch in noch unreifen Knochen umgewandelt, welcher den Kieferknochen und auch die angrenzenden Zähne stabilisiert. Nach seiner Ausreifung passt sich das Gewebe schließlich dem umgebenden Knochen an. Das Erscheinungsbild des Zahnfaches während dieses Vorgangs durchläuft verschiedene Stadien, welche in der vorliegenden Studie anhand von klinischen Röntgenaufnahmen rezenter Patienten sowie durch Untersuchungen an archäologischen Skelettserien identifiziert wurden. Die Heilungsvorgänge im Zahnfach können in eine prä-ossale Phase (innerhalb einer Woche nach Zahnverlust), eine Verknöcherungsphase (etwa 14 Wochen nach Zahnverlust) und eine ossifizierte bzw. komplett verheilte Phase (mindestens 29 Wochen nach Zahnverlust) eingeteilt werden. Etliche Faktoren – wie etwa die Resorption des Interdentalseptums, der Zustand des Alveolarknochens oder das Individualgeschlecht – können den normalen Heilungsprozess signifikant beschleunigen oder hemmen und so Unterschiede von bis zu 19 Wochen verursachen. Weitere Variablen wirkten sich nicht signifikant auf den zeitlichen Rahmen des Heilungsprozesse aus. Relevante Abhängigkeiten zwischen verschiedenen Variabeln wurden ungeachtet der Alveolenauffüllung ebenfalls getestet. Gruppen von unabhängigen Variabeln wurden im Hinblick auf Auffüllungsgrad und TSL in multivariablen Modellen untersucht. Mit Hilfe dieser Ergebnisse ist eine grobe Einschätzung der Zeitspanne nach einem Zahnverlust in Wochen möglich, wobei die Einbeziehung weiterer Parameter eine höhere Präzision ermöglicht. rnrnObwohl verschiedene dentale Pathologien in dieser Studie berücksichtigt wurden, sollten zukünftige Untersuchungen genauer auf deren potenzielle Einflussnahme auf den alveolaren Heilungsprozess eingehen. Der kausale Zusammenhang einiger Variablen (wie z. B. Anwesenheit von Nachbarzähnen oder zahnmedizinische Behandlungen), welche die Geschwindigkeit der Heilungsrate beeinflussen, wäre von Bedeutung für zukünftige Untersuchungen des oralen Knochengewebes. Klinische Vergleichsstudien an forensischen Serien mit bekannter TSL oder an einer sich am Anfang des Heilungsprozesses befindlichen klinischen Serie könnten eine Bekräftigung dieser Ergebnisse liefern.

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In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

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The paper deals with batch scheduling problems in process industries where final products arise from several successive chemical or physical transformations of raw materials using multi–purpose equipment. In batch production mode, the total requirements of intermediate and final products are partitioned into batches. The production start of a batch at a given level requires the availability of all input products. We consider the problem of scheduling the production of given batches such that the makespan is minimized. Constraints like minimum and maximum time lags between successive production levels, sequence–dependent facility setup times, finite intermediate storages, production breaks, and time–varying manpower contribute to the complexity of this problem. We propose a new solution approach using models and methods of resource–constrained project scheduling, which (approximately) solves problems of industrial size within a reasonable amount of time.

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This paper is concerned with the modelling of storage configurations for intermediate products in process industries. Those models form the basis of algorithms for scheduling chemical production plants. Different storage capacity settings (unlimited, finite, and no intermediate storage), storage homogeneity settings (dedicated and shared storage), and storage time settings (unlimited, finite, and no wait) are considered. We discuss a classification of storage constraints in batch scheduling and show how those constraints can be integrated into a general production scheduling model that is based on the concept of cumulative resources.

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The interactions among three important issues involved in the implementation of logic programs in parallel (goal scheduling, precedence, and memory management) are discussed. A simplified, parallel memory management model and an efficient, load-balancing goal scheduling strategy are presented. It is shown how, for systems which support "don't know" non-determinism, special care has to be taken during goal scheduling if the space recovery characteristics of sequential systems are to be preserved. A solution based on selecting only "newer" goals for execution is described, and an algorithm is proposed for efficiently maintaining and determining precedence relationships and variable ages across parallel goals. It is argued that the proposed schemes and algorithms make it possible to extend the storage performance of sequential systems to parallel execution without the considerable overhead previously associated with it. The results are applicable to a wide class of parallel and coroutining systems, and they represent an efficient alternative to "all heap" or "spaghetti stack" allocation models.

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The analysis of concurrent constraint programs is a challenge due to the inherently concurrent behaviour of its computational model. However, most implementations of the concurrent paradigm can be viewed as a computation with a fixed scheduling rule which suspends some goals so that their execution is postponed until some condition awakens them. For a certain kind of properties, an analysis defined in these terms is correct. Furthermore, it is much more tractable, and in addition can make use of existing analysis technology for the underlying fixed computation rule. We show how this can be done when the starting point is a framework for the analysis of sequential programs. The resulting analysis, which incorporates suspensions, is adequate for concurrent models where concurrency is localized, e.g. the Andorra model. We refine the analysis for this particular case. Another model in which concurrency is preferably encapsulated, and thus suspensions are local to parts of the computation, is that of CIAO. Nonetheless, the analysis scheme can be generalized to models with global concurrency. We also sketch how this could be done, and we show how the resulting analysis framework could be used for analyzing typical properties, such as suspensión freeness.

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In this paper, we examine the issue of memory management in the parallel execution of logic programs. We concentrate on non-deterministic and-parallel schemes which we believe present a relatively general set of problems to be solved, including most of those encountered in the memory management of or-parallel systems. We present a distributed stack memory management model which allows flexible scheduling of goals. Previously proposed models (based on the "Marker model") are lacking in that they impose restrictions on the selection of goals to be executed or they may require consume a large amount of virtual memory. This paper first presents results which imply that the above mentioned shortcomings can have significant performance impacts. An extension of the Marker Model is then proposed which allows flexible scheduling of goals while keeping (virtual) memory consumption down. Measurements are presented which show the advantage of this solution. Methods for handling forward and backward execution, cut and roll back are discussed in the context of the proposed scheme. In addition, the paper shows how the same mechanism for flexible scheduling can be applied to allow the efficient handling of the very general form of suspension that can occur in systems which combine several types of and-parallelism and more sophisticated methods of executing logic programs. We believe that the results are applicable to many and- and or-parallel systems.