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

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 Innovación TIN2004-06689-C03-03Ministerio de Ciencia e Innovación TIN2007-67843-C06-0

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

© 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

A lexicographical dynamic flow model for relief operations

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

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

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

Impact of internet of things (IoT) in disaster management: a task-technology fit perspective

YesDisaster management aims to mitigate the potential damage from the disasters, ensure immediate and suitable assistance to the victims, and attain effective and rapid recovery. These objectives require a planned and effective rescue operation post such disasters. Different types of information about the impact of the disaster are, hence, required for planning an effective and immediate relief operation. The IoT technology available today is quite mature and has the potential to be very useful in disaster situations. This paper analyzes the requirements for planning rescue operation for such natural disasters and proposes an IoT based solution to cater the identified requirements. The proposed solution is further validated using the task-technology fit (TTF) approach for analyzing the significance of the adoption of IoT technology for disaster management. Results from the exploratory study established the core dimensions of the task requirements and the TTF constructs. Results from the confirmatory factor analysis using PLS path modelling, further, suggest that both task requirements and IoT technology have significant impact on the IoT TTF in the disaster management scenario. This paper makes significant contributions in the development of appropriate constructs for modeling TTF for IoT Technology in the context of disaster management

Vibration analysis of rotor blades of a farm wind-power plant

In wind-power plants like in all engineering structures, vibrations are taken into consideration in design phases in order to avoid resonance. This condition occurs when the frequency of the exciting force coincides with one of the natural frequencies of system, which causes dangerously large amplitudes. in the present study, natural frequencies of the Rotor blades of NACA (National Advisory Committee for Aeronautics) 4415 and NASA/Langley LS(1) 421MOD series of wind-power plants that deliver energy to be consumed by a farm family with four persons are calculated. Therefore, after designing the rotors, their natural frequencies are determined first by Rayleigh‘s Method and next by finite element method. Further for both rotor blades, resonance analysis is carried out by the found excitation of external forces

Clinical Applications of Evoked Potential Continuous Loop Averaging Deconvolution (CLAD)

Using the new Continuous Loop Averaging Deconvolution (CLAD) acquisition technique, it is now possible to record evoked potentials at very high stimulation rates. The CLAD technique allows the experimenter to tailor the stimulation sequences to fit his specific application to unwrap overlapping responmses at high rates. CLAD sequences can be designed to reduce physiological adaptation effects and to control the noise shaping effect of the deconvolution process. This study shows examples of promising clinical applications of CLAD using Electrocochleograms (ECochGm), Auditory Brainstem Responses (ABR), Auditory Middle Latency Responses (AMLR): In the first example CLAD was applied to record TransTympanic (TT) ECochGm at conventional and high rates in Meniere’s patients. These high-rate ECochGs revealed distinctive physiological patterns not previously observed at conventional rates. Regarding the ABRs, custom CLAD sequences were designed to simultaneously provide high Signal to Noise Ratio (SNR) ABRs and 80-Hz Auditory Steady State Responses (ASSR). The use of these sequences enabled the investigators to assess the hearing in guinea pigs exposed to cochlear implant electrode insertion trauma. A similar technique was applied in normal human subjects to unveil the generation mechanisms of amplitude modulated ASSR. CLAD was also used to record 40-Hz MLRs in normal awake subjects and patients under anesthesia; the ASSR showed to be a composite of the evoked, transient waveforms. Thus CLAD was able to explain the inability of 5- or 10-Hz AMLRs to predict the 40-Hz ASSR in anesthesia