976 resultados para Time windows


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This study addresses a vehicle routing problem with time windows, accessibility restrictions on customers, and a fleet that is heterogeneous with regard to capacity and average speed. A vehicle can performmultiple routes per day, all starting and ending at a single depot, and it is assigned to a single driverwhose totalwork hours are limited.Acolumn generation algorithmis proposed.The column generation pricing subproblem requires a specific elementary shortest path problem with resource constraints algorithm to address the possibility for each vehicle performingmultiple routes per day and to address the need to set the workday’s start time within the planning horizon. A constructive heuristic and a metaheuristic based on tabu search are also developed to find good solutions.

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In this paper we propose two cooperation schemes to compose new parallel variants of the Variable Neighborhood Search (VNS). On the one hand, a coarse-grained cooperation scheme is introduced which is well suited for being enhanced with a solution warehouse to store and manage the so far best found solutions and a self-adapting mechanism for the most important search parameters. This makes an a priori parameter tuning obsolete. On the other hand, a fine-grained scheme was designed to reproduce the successful properties of the sequential VNS. In combination with the use of parallel exploration threads all of the best solutions and 11 out of 20 new best solutions for the Multi Depot Vehicle Routing Problem with Time Windows were found.

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As an immune-inspired algorithm, the Dendritic Cell Algorithm (DCA), produces promising performance in the field of anomaly detection. This paper presents the application of the DCA to a standard data set, the KDD 99 data set. The results of different implementation versions of the DCA, including antigen multiplier and moving time windows, are reported. The real-valued Negative Selection Algorithm (NSA) using constant-sized detectors and the C4.5 decision tree algorithm are used, to conduct a baseline comparison. The results suggest that the DCA is applicable to KDD 99 data set, and the antigen multiplier and moving time windows have the same effect on the DCA for this particular data set. The real-valued NSA with contant-sized detectors is not applicable to the data set. And the C4.5 decision tree algorithm provides a benchmark of the classification performance for this data set.

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This article augments Resource Dependence Theory with Real Options reasoning in order to explain time bounds specification in strategic alliances. Whereas prior work has found about a 50/50 split between alliances that are time bound and those that are open-ended, their substantive differences and antecedents are ill understood. To address this, we suggest that the two alliance modes present different real options trade-offs in adaptation to environmental uncertainty: ceteris paribus, time-bound alliances are likely to provide abandonment options over open-ended alliances, but require additional investments to extend the alliance when this turns out to be desirable after formation. Open-ended alliances are likely to provide growth options over open-ended alliances, but they demand additional effort to abandon the alliance if post-formation circumstances so desire. Therefore, we expect time bounds specification to be a function of environmental uncertainty: organizations in more uncertain environments will be relatively more likely to place time bounds on their strategic alliances. Longitudinal archival and survey data collected amongst 39 industry clusters provides empirical support for our claims, which contribute to the recent renaissance of resource dependence theory by specifying the conditions under which organizations choose different time windows in strategic partnering.

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Are persistent marketing effects most likely to appear right after the introduction of a product? The authors give an affirmative answer to this question by developing a model that explicitly reports how persistent and transient marketing effects evolve over time. The proposed model provides managers with a valuable tool to evaluate their allocation of marketing expenditures over time. An application of the model to many pharmaceutical products, estimated through (exact initial) Kalman filtering, indicates that both persistent and transient effects occur predominantly immediately after a brand's introduction. Subsequently, the size of the effects declines. The authors theoretically and empirically compare their methodology with methodology based on unit root testing and demonstrate that the need for unit root tests creates difficulties in applying conventional persistence modeling. The authors recommend that marketing models should either accommodate persistent effects that change over time or be applied to mature brands or limited time windows only.

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In this paper techniques for scheduling additional train services (SATS) are considered as is train scheduling involving general time window constraints, fixed operations, maintenance activities and periods of section unavailability. The SATS problem is important because additional services must often be given access to the railway and subsequently integrated into current timetables. The SATS problem therefore considers the competition for railway infrastructure between new services and existing services belonging to the same or different operators. The SATS problem is characterised as a hybrid job shop scheduling problem with time window constraints. To solve this problem constructive algorithm and metaheuristic scheduling techniques that operate upon a disjunctive graph model of train operations are utilised. From numerical investigations the proposed framework and associated techniques are tested and shown to be effective.

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It’s fast approaching the end of the year and the festive season, and I have a few things on my mind. First, how I’ll fit in all of my holiday plans and projects within my period of leave, which always seems to pass oh so quickly! But more important are the two issues of global financial uncertainty and safe travel. Judging by what is in the media, it appears to be proving difficult for any self respecting financial industry specialist to define and grapple with the so-called current economic crisis, let alone those of us who have not been formally and extensively schooled in the sciences of finance and economics. Perhaps the latter is even more of a “black art” than the discipline of transport planning. The situation has affected all of us with our superannuation and/or share portfolios; however, judging by the still-crowded shopping centres in many areas, the downstream general economic impacts appear to be less serious in Australia than in other developed countries, even with the significant market fluctuations taking place. There are many important decisions facing Australian governments, from the top down, on how they manage their budgets and spending. Infrastructure spending is in competition with other necessities such as the public health system and education. But it appears that infrastructure is an avenue of public spending that, over all time windows, may be able to significantly bolster local economies and that of the nation as a whole. This, however, is against the spectre of deficits. I would suggest that now, more than ever, we as transport and other professionals within the system, should use our knowledge and experience to take a key role in helping government and the private sector make sound decisions on infrastructure planning, delivery and management.

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Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.

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Business processes are prone to continuous and unexpected changes. Process workers may start executing a process differently in order to adjust to changes in workload, season, guidelines or regulations for example. Early detection of business process changes based on their event logs – also known as business process drift detection – enables analysts to identify and act upon changes that may otherwise affect process performance. Previous methods for business process drift detection are based on an exploration of a potentially large feature space and in some cases they require users to manually identify the specific features that characterize the drift. Depending on the explored feature set, these methods may miss certain types of changes. This paper proposes a fully automated and statistically grounded method for detecting process drift. The core idea is to perform statistical tests over the distributions of runs observed in two consecutive time windows. By adaptively sizing the window, the method strikes a trade-off between classification accuracy and drift detection delay. A validation on synthetic and real-life logs shows that the method accurately detects typical change patterns and scales up to the extent it is applicable for online drift detection.

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The “distractor-frequency effect” refers to the finding that high-frequency (HF) distractor words slow picture naming less than low-frequency distractors in the picture–word interference paradigm. Rival input and output accounts of this effect have been proposed. The former attributes the effect to attentional selection mechanisms operating during distractor recognition, whereas the latter attributes it to monitoring/decision mechanisms operating on distractor and target responses in an articulatory buffer. Using high-density (128-channel) EEG, we tested hypotheses from these rival accounts. In addition to conducting stimulus- and response-locked whole-brain corrected analyses, we investigated the correct-related negativity, an ERP observed on correct trials at fronto-central electrodes proposed to reflect the involvement of domain general monitoring. The wholebrain ERP analysis revealed a significant effect of distractor frequency at inferior right frontal and temporal sites between 100 and 300-msec post-stimulus onset, during which lexical access is thought to occur. Response-locked, region of interest (ROI) analyses of fronto-central electrodes revealed a correct-related negativity starting 121 msec before and peaking 125 msec after vocal onset on the grand averages. Slope analysis of this component revealed a significant difference between HF and lowfrequency distractor words, with the former associated with a steeper slope on the time windowspanning from100 msec before to 100 msec after vocal onset. The finding of ERP effects in time windows and components corresponding to both lexical processing and monitoring suggests the distractor frequency effect is most likely associated with more than one physiological mechanism.

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The optimization of a near-circular low-Earth-orbit multispacecraft refueling problem is studied. The refueling sequence, service time, and orbital transfer time are used as design variables, whereas the mean mission completion time and mean propellant consumed by orbital maneuvers are used as design objectives. The J2 term of the Earth's nonspherical gravity perturbation and the constraints of rendezvous time windows are taken into account. A hybridencoding genetic algorithm, which uses normal fitness assignment to find the minimum mean propellant-cost solution and fitness assignment based on the concept of Pareto-optimality to find multi-objective optimal solutions, is presented. The proposed approach is demonstrated for a typical multispacecraft refueling problem. The results show that the proposed approach is effective, and that the J2 perturbation and the time-window constraints have considerable influences on the optimization results. For the problems in which the J2 perturbation is not accounted for, the optimal refueling order can be simply determined as a sequential order or as the order only based on orbitalplane differences. In contrast, for the problems that do consider the J2 perturbation, the optimal solutions obtained have a variety of refueling orders and use the drift of nodes effectively to reduce the propellant cost for eliminating orbital-plane differences. © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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In this paper, the codes of Pattern Informatics (PI) method put forward by Rundle et al. have been worked out according to their algorithm published, and the retrospective forecast of PI method to North China (28.0 degrees-42.0 degrees N, 108.0 degrees-125.0 degrees E) and to Southwest China (22.0 degrees-28.3 degrees N, 98.0 degrees-106.0 degrees E) has been tested. The results show that the hit rates in different regions show a great difference. In Southwest China, 32 earthquakes with M(L)5.0 or larger have occurred during the predicted time period 2000-2007, and 26 out of the 32 earthquakes occurred in or near the hot spots. In North China, the total number of M(L)5.0 or larger was 12 during the predicted time period 2000-2007, and only 3 out of the 12 earthquakes occurred in or near the hot spots. From our results, we hold that if the PI method could be applied to all kinds of regions, the parameters associated with time points and time windows should be chosen carefully to obtain the higher hit rate. We also found that the aftershocks in a strong earthquake sequence affect the PI results obviously. Copyright (c) 2009 John Wiley & Sons, Ltd.

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In this paper, the codes of Pattern Informatics (PI) method put forward by Rundle et al. have been worked out according to their algorithm published, and the retrospective forecast of PI method to North China (28.0 degrees-42.0 degrees N, 108.0 degrees-125.0 degrees E) and to Southwest China (22.0 degrees-28.3 degrees N, 98.0 degrees-106.0 degrees E) has been tested. The results show that the hit rates in different regions show a great difference. In Southwest China, 32 earthquakes with M(L)5.0 or larger have occurred during the predicted time period 2000-2007, and 26 out of the 32 earthquakes occurred in or near the hot spots. In North China, the total number of M(L)5.0 or larger was 12 during the predicted time period 2000-2007, and only 3 out of the 12 earthquakes occurred in or near the hot spots. From our results, we hold that if the PI method could be applied to all kinds of regions, the parameters associated with time points and time windows should be chosen carefully to obtain the higher hit rate. We also found that the aftershocks in a strong earthquake sequence affect the PI results obviously. Copyright (c) 2009 John Wiley & Sons, Ltd.