127 research outputs found

    A Hybrid Model for Dynamic Simulation of Custom Software Projects in a Multiproject Environment

    Get PDF
    This paper describes SimHiProS, a hybrid simulation model of software production. The goal is to gain insight on the dynamics induced by resource sharing in multiproject management. In order to achieve it the hierarchy of decisions in a multiproject organization is modeled and some resource allocation methods based on algorithms from the OR/AI domain are used. Other critical issues such as the hybrid nature of software production and the effects of measurement and control are also incorporated in the model. Some first results are presented.Ministerio de Ciencia e InnovaciĂłn TIN2004-06689-C03-03Ministerio de Ciencia e InnovaciĂłn TIN2007-67843-C06-0

    Event Monitoring System to Classify Unexpected Events for Production Planning

    Full text link
    [EN] Production planning prepares companies to a future production scenario. The decision process followed to obtain the production plan considers real data and estimated data of this future scenario. However, these plans can be affected by unexpected events that alter the planned scenario and in consequence, the production planning. This is especially critical when the production planning is ongoing. Thus providing information about these events can be critical to reconsider the production planning. We herein propose an event monitoring system to identify events and to classify them into different impact levels. The information obtained from this system helps to build a risk matrix, which determines the significance of the risk from the impact level and the likelihood. A prototype has been built following this proposal.This research has been carried out in the framework of the project GV/2014/010 funded by the Generalitat Valenciana (Identificacion de la informacion proporcionada por los nuevos sistemas de deteccion accesibles mediante internet en el ambito de las "sensing enterprises" para la mejora de la toma de decisiones en la planificacion de la produccion).Boza, A.; Alarcón Valero, F.; Alemany Díaz, MDM.; Cuenca, L. (2017). Event Monitoring System to Classify Unexpected Events for Production Planning. Lecture Notes in Business Information Processing. 291:140-154. https://doi.org/10.1007/978-3-319-62386-3_7S140154291Barták, R.: On the boundary of planning and scheduling: a study (1999)Buzacott, J.A., Corsten, H., Gössinger, R., Schneider, H.M.: Production Planning and Control: Basics and Concepts. Oldenbourg Wissenschaftsverlag, München (2012)Özdamar, L., Bozyel, M.A., Birbil, S.I.: A hierarchical decision support system for production planning (with case study). Eur. J. Oper. Res. 104(3), 403–422 (1998)Van Wezel, W., Van Donk, D.P., Gaalman, G.: The planning flexibility bottleneck in food processing industries. J. Oper. Manag. 24(3), 287–300 (2006)Shamsuzzoha, A.H., Rintala, S., Cunha, P.F., Ferreira, P.S., Kankaanpää, T., Maia Carneiro, L.: Event monitoring and management process in a non-hierarchical business network. In: Intelligent Non-hierarchical Manufacturing Networks, pp. 349–374. Wiley, Hoboken (2013)Sacala, I.S., Moisescu, M.A., Repta, D.: Towards the development of the future internet based enterprise in the context of cyber-physical systems. In: 19th International Conference on Control Systems and Computer Science, CSCS 2013, pp. 405–412 (2013)Chen, K.C.: Decision support system for tourism development: system dynamics approach. J. Comput. Inf. Syst. 45(1), 104–112 (2004)Boza, A., Alemany, M.M.E., Vicens, E., Cuenca, L.: Event management in decision-making processes with decision support systems. In: 5th International Conference on Computers Communications and Control (2014)Liao, S.-H.: Expert system methodologies and applications–a decade review from 1995 to 2004. Expert Syst. Appl. 28(1), 93–103 (2005)ISO: 73: 2009: Risk management vocabulary. International Organization for Standardization (2009)Chan, F.T.S., Au, K.C., Chan, P.L.Y.: A decision support system for production scheduling in an ion plating cell. Expert Syst. Appl. 30(4), 727–738 (2006)Weinstein, L., Chung, C.-H.: Integrating maintenance and production decisions in a hierarchical production planning environment. Comput. Oper. Res. 26(10–11), 1059–1074 (1999)Poon, T.C., Choy, K.L., Chan, F.T.S., Lau, H.C.W.: A real-time production operations decision support system for solving stochastic production material demand problems. Expert Syst. Appl. 38(5), 4829–4838 (2011)SAP AG: SAP AG 2014. Next-Generation Business and the Internet of Things. Studio SAP | 27484enUS (14/03) (2014)Carneiro, L.M., Cunha, P., Ferreira, P.S., Shamsuzzoha, A.: Conceptual framework for non-hierarchical business networks for complex products design and manufacturing. Procedia CIRP 7, 61–66 (2013)Vargas, A., Cuenca, L., Boza, A., Sacala, I., Moisescu, M.: Towards the development of the framework for inter sensing enterprise architecture. J. Intell. Manuf. 26, 55–72 (2016)Barash, G., Bartolini, C., Wu, L.: Measuring and improving the performance of an IT support organization in managing service incidents, pp. 11–18 (2007)Liu, R., Kumar, A., van der Aalst, W.: A formal modeling approach for supply chain event management. Decis. Support Syst. 43(3), 761–778 (2007)Söderholm, A.: Project management of unexpected events. Int. J. Proj. Manag. 26(1), 80–86 (2008)Bearzotti, L.A., Salomone, E., Chiotti, O.J.: An autonomous multi-agent approach to supply chain event management. Int. J. Prod. Econ. 135(1), 468–478 (2012)Baron, M.M., Pate-Cornell, M.E.: Designing risk-management strategies for critical engineering systems. IEEE Trans. Eng. Manag. 46(1), 87–100 (1999)Bartolini, C., Stefanelli, C., Tortonesi, M.: SYMIAN: analysis and performance improvement of the IT incident management process. IEEE Trans. Netw. Serv. Manag. 7(3), 132–144 (2010)Cox Jr., L.A.: What’s wrong with risk matrices? Risk Anal. Int. J. 28(2), 497–512 (2008)Shim, J.P., Warkentin, M., Courtney, J.F., Power, D.J., Sharda, R., Carlsson, C.: Past, present, and future of decision support technology. Decis. Support Syst. 33(2), 111–126 (2002)Steiger, D.M.: Enhancing user understanding in a decision support system: a theoretical basis and framework (2015). http://dx.doi.org/10.1080/07421222.1998.11518214Turban, E., Aronson, J., Liang, T.-P.: Decision Support Systems and Intelligent Systems, 7th edn. Pearson Prentice Hall, Upper Saddle River (2005)Turban, E., Watkins, P.R.: Integrating expert systems and decision support systems, 10, 121–136 (1986)Cohen, D., Asín, E.: Sistemas de información para los negocios: un enfoque de toma de decisiones. McGraw-Hill, New York City (2001)Boza, A., Cortés, B., Alemany, M.M.E., Vicens, E.: Event monitoring software application for production planning systems. In: Cortés, P., Maeso-González, E., Escudero-Santana, A. (eds.) Enhancing Synergies in a Collaborative Environment. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-14078-0_14Boza, A., Alarcón, F., Alemany, M.M.E., Cuenca, L.: Event classification system to reconsider the production planning. In: Proceedings of the 18th International Conference on Enterprise Information Systems, pp. 82–88 (2016)Maximal Software: What is MPL? (2016). http://www.maximalsoftware.com/mpl/what.htm

    A novel flexible model for lot sizing and scheduling with non-triangular, period overlapping and carryover setups in different machine configurations

    Get PDF
    © 2017, Springer Science+Business Media New York. This paper develops and tests an efficient mixed integer programming model for capacitated lot sizing and scheduling with non-triangular and sequence-dependent setup times and costs incorporating all necessary features of setup carryover and overlapping on different machine configurations. The model’s formulation is based on the asymmetric travelling salesman problem and allows multiple lots of a product within a period. The model conserves the setup state when no product is being processed over successive periods, allows starting a setup in a period and ending it in the next period, permits ending a setup in a period and starting production in the next period(s), and enforces a minimum lot size over multiple periods. This new comprehensive model thus relaxes all limitations of physical separation between the periods. The model is first developed for a single machine and then extended to other machine configurations, including parallel machines and flexible flow lines. Computational tests demonstrate the flexibility and comprehensiveness of the proposed models

    Binaural interaction of the auditory brain-stem potentials and middle latency auditory evoked potentials in infants and adults

    Full text link
    Binaural interactions in brain-stem auditory evoked potentials and in middle latency auditory evoked potentials were studied in 18 normal hearing adults and 10 normal term infants. Binaural interactions at the times of ABR waves V and VI were comparable in term infants and adults. Binaural interaction during the time domain of the middle latency auditory evoked potentials was the greatest at N20 in term infants and at N40 in adults. Measurement of binaural interaction during maturation may be a useful tool in assessing neurologically affected infants

    A lexicographical dynamic flow model for relief operations

    Get PDF
    Emergency management is a highly relevant area of interest in operations research. Currently the area is undergoing widespread development. Furthermore, recent disasters have highlighted the importance of disaster management, in order to alleviate the suffering of vulnerable people and save lives. In this context, the problem of designing plans for the distribution of humanitarian aid according to the preferences of the decision maker is crucial. In this paper, a lexicographical dynamic flow model to solve this problem is presented, extending a previously introduced static flow model. The new model is validated in a realistic case study and a computational study is performed to compare both models, showing how they can be coordinated to improve their overall performance

    Emergency logistics for wildfire suppression based on forecasted disaster evolution

    Get PDF
    This paper aims to develop a two-layer emergency logistics system with a single depot and multiple demand sites for wildfire suppression and disaster relief. For the first layer, a fire propagation model is first built using both the flame-igniting attributes of wildfires and the factors affecting wildfire propagation and patterns. Second, based on the forecasted propagation behavior, the emergency levels of fire sites in terms of demand on suppression resources are evaluated and prioritized. For the second layer, considering the prioritized fire sites, the corresponding resource allocation problem and vehicle routing problem (VRP) are investigated and addressed. The former is approached using a model that can minimize the total forest loss (from multiple sites) and suppression costs incurred accordingly. This model is constructed and solved using principles of calculus. To address the latter, a multi-objective VRP model is developed to minimize both the travel time and cost of the resource delivery vehicles. A heuristic algorithm is designed to provide the associated solutions of the VRP model. As a result, this paper provides useful insights into effective wildfire suppression by rationalizing resources regarding different fire propagation rates. The supporting models can also be generalized and tailored to tackle logistics resource optimization issues in dynamic operational environments, particularly those sharing the same feature of single supply and multiple demands in logistics planning and operations (e.g., allocation of ambulances and police forces). © 2017 The Author(s

    Logistics service provider selection for disaster preparation: a socio-technical systems perspective

    Get PDF
    Since 1990s, the world has seen a lot of advances in providing humanitarian aid through sophisticated logistics operations. The current consensus seems to be that humanitarian relief organizations (HROs) can improve their relief operations by collaborating with logistics service providers (CLSPs) in the commercial sector. The question remains: how can HROs select the most appropriate CLSP for disaster preparation? Despite its practical significance, no explicit effort has been done to identify the criteria/factors in prioritising and selecting a CLSP for disaster relief. The present study aims to address this gap by consolidating the list of criteria from a socio-technical systems (STS) perspective. Then, to handle the interdependence among the criteria derived from the STS, we develop a hybrid multi-criteria decision making model for CLSP selection in the disaster preparedness stage. The proposed model is then evaluated by a real-life case study, providing insights into the decision-makers in both HROs and CLSPs

    Swift trust and commitment: the missing links for humanitarian supply chain coordination?

    Get PDF
    Coordination among actors in a humanitarian relief supply chain decides whether a relief operation can be or successful or not. In humanitarian supply chains, due to the urgency and importance of the situation combined with scarce resources, actors have to coordinate and trust each other in order to achieve joint goals. This paper investigated empirically the role of swift trust as mediating variable for achieving supply chain coordination. Based on commitment-trust theory we explore enablers of swift-trust and how swift trust translates into coordination through commitment. Based on a path analytic model we test data from the National Disaster Management Authority of India. Our study is the first testing commitment-trust theory (CTT) in the humanitarian context, highlighting the importance of swift trust and commitment for much thought after coordination. Furthermore, the study shows that information sharing and behavioral uncertainty reduction act as enablers for swift trust. The study findings offer practical guidance and suggest that swift trust is a missing link for the success of humanitarian supply chains
    • …
    corecore