Search

This paper aims to solve large continuous p-centre problems optimally by re-examining a recent relaxation-based algorithm. The algorithm is strengthened by adding four mathematically supported enhancements to improve its efficiency. This revised relaxation algorithm yields a massive reduction in computational time enabling for the first time larger data-sets to be solved optimally (e.g., up to 1323 nodes). The enhanced algorithm is also shown to be flexible as it can be easily adapted to optimally solve related practical location problems that are frequently faced by senior management when making strategic decisions. These include the -neighbour p-centre problem and the conditional p-centre problem. A scenario analysis using variable is also performed to provide further managerial insights. [ABSTRACT FROM AUTHOR]

In this paper, the Rayleigh-Lindley (RL) distribution is introduced, obtained by compounding the Rayleigh and Lindley discrete distributions, where the compounding procedure follows an approach similar to the one previously studied by Adamidis and Loukas in some other contexts. The resulting distribution is a two-parameter model, which is competitive with other parsimonious models such as the gamma and Weibull distributions. We study some properties of this new model such as the moments and the mean residual life. The estimation was approached via EM algorithm. The behavior of these estimators was studied in finite samples through a simulation study. Finally, we report two real data illustrations in order to show the performance of the proposed model versus other common two-parameter models in the literature. The main conclusion is that the model proposed can be a valid alternative to other competing models well established in the literature. [ABSTRACT FROM AUTHOR]

The stochastic realisation problem is associated with fitting a state-space model to a given data-set so that the second-order statistics of the output of the system match those of the data. This problem has been well studied and documented in the 1-D case, but unfortunately not so in the 2-D case, despite the similarities. Until now, the main reason behind the lack of 2-D stochastic realisation algorithms is the fact that there is a strong coupling between horizontal and vertical states, which are difficult to separate. The only known way to separate the states is to assume the model to be causal, recursive, and separable-in-denominator (CRSD). Nevertheless, there is currently no known algorithm that can solve the general 2-D stochastic realisation problem. Such problem arises naturally in image modelling, where, given an image, one needs to fit a 2-D Kalman filter model to it. In this paper, we introduce a 2-D stochastic realisation algorithm for state-space models in the general 2-D Roesser form without using the CRSD assumption. The algorithm constructs a positive real 2-D Kalman filter model. We test the algorithm with three case studies, one of which is an image example. [ABSTRACT FROM AUTHOR]

In this paper, we present an interior point method for nonlinear programming that avoids the use of penalty function or filter. We use an adaptively perturbed primal dual interior point framework to computer trial steps and a central path technique is used to keep the iterate bounded away from 0 and not to deviate too much from the central path. A trust-funnel-like strategy is adopted to drive convergence. We also use second-order correction (SOC) steps to achieve fast local convergence by avoiding Maratos effect. Furthermore, the presented algorithm can avoid the blocking effect. It also does not suffer the blocking of productive steps that other trust-funnel-like algorithm may suffer. We show that, under second-order sufficient conditions and strict complementarity, the full Newton step (combined with an SOC step) will be accepted by the algorithm near the solution, and hence the algorithm is superlinearly local convergent. Numerical experiments results, which are encouraging, are reported. [ABSTRACT FROM AUTHOR]

The features related to the real world data may be redundant and erroneous in nature. The vital role of feature selection (FS) in handling such type of features cannot be ignored in the area of computational learning. The two most commonly used objectives for FS are the maximisation of the accuracy and minimisation of the number of features. This paper presents an Elitism-based Multi-objective Differential Evolution algorithm for FS and the novelty lies in the searching process which uses Minkowski Score (MS) and simultaneously optimises three objectives. The MS is considered as the third objective to keep track of the feature subset which is capable enough to produce a good classification result even if the average accuracy is poor. Extreme Learning Machine because of its fast learning speed and high efficiency has been considered with this multi-objective approach as a classifier for FS. Twenty-one benchmark datasets have been considered for performance evaluation. Moreover, the selected feature subsets are tested using 10-fold cross-validation. A comparative analysis of the proposed approach with two classical models, three single objective algorithms, and four multi-objective algorithms has been carried out to test the efficacy of the model. [ABSTRACT FROM AUTHOR]

Fatigue has become an increasing problem in our modern society. Using MATLAB as a generic modelling tool, a fatigue model was developed based on an existing one and compared with a commercial fatigue software for prediction of cognitive performance under total and partial sleep deprivation. The flexibility of our fatigue model allowed additions of new algorithms and mechanisms for non-sleep factors and countermeasures and thus improved model predictions and usability for both civilian and military applications. This was demonstrated by model simulations of various scenarios and comparison with experimental studies. Our future work will be focused on model validation and integration with other modelling tools. Practitioner Summary: Mental fatigue affects health, safety and quality of life in our modern society. In this paper, we reported a cognitive fatigue model based on existing models with newly incorporated components taking both the operator’s state of alertness and task demand into account. The model provided the additional capability for prediction of cognitive performance in scenarios involving pharmaceutical countermeasures, different task demands and shift work. [ABSTRACT FROM AUTHOR]

In this paper, we present the analytical foundations for modelling the staircase traversal of convex polygonal surfaces by a tool in the form of a circular disk. Based on these foundations, we next develop a mathematical model and an algorithm for a near optimal tool path in a staircase traversal of convex polygonal surfaces. We compare this algorithm---which is called OPTPATH--with two existing algorithms. This comparison confirms that OPTPATH performs better than the other two test algorithms. The OPTPATH algorithm can be used for staircase traversal with or without overlap between successive sweep passes and with or without rapid traversal in edge passes. This generality of OPTPATH allows its application to several manufacturing problems such as face and pocket milling, robotic deburring, rapid prototyping, and robotic spray painting. The results of the theorems presented in the paper can be helpful in designing new algorithms as well as in improving some of the existing algorithms for optimizing tool path in staircase traversal of convex polygonal surfaces. [ABSTRACT FROM AUTHOR]

The shipyard block erection system (SBES) is a typical discrete-event dynamic system. To model multiprocessing paths and a concurrent assembly procedure, a timed Petri net (TPN) is proposed. The definition of a Petri net is extended to accord with the real-world SBES organisation. The basic TPN modules are presented to model the corresponding variable structures in the SBES, and then the scheduling model of the whole SBES is easily constructed. A modified discrete particle swarm optimisation (PSO) based on the reachability analysis of Petri nets is developed for scheduling of the SBES. In the proposed algorithm, particles are coded by welding transitions and selecting places of the TPN model, and then the collaboration and competition of particle individuals is simulated by crossover and mutation operators in a genetic algorithm. Numerical simulation suggests that the proposed TPN–PSO scheduler can provide an improvement over the conventional scheduling method. Finally, a case study of the optimisation of a back block erection process is provided to illustrate the effectiveness of the method. [ABSTRACT FROM PUBLISHER]

The conditional diagnosis is a very important measure of the reliability and the fault-tolerance of networks. The ‘condition’ means that no faulty set contains all neighbours of any node. Under this assumption, for any systemG, every component ofhas more than 1 node, whereFis the faulty set ofG. Theg-extra conditional diagnosability is defined under the assumption that every component ofhas more thannodes. ‘A system with at mosttfaulty nodes is defined as sequentiallyt-diagnosable if at least one faulty node can be repaired, so that the testing can be continued using the repaired node to eventually diagnose all faulty nodes’ [E.P. Duarte Jr., R.P. Ziwich, and L.C.P. Albini,A survey of comparison-based system-level diagnosis, ACM Comput. Surv. 43(3) (2011), article 22]. To increase the degree of the sequentialt-diagnosability of a system, sequential-diagnosis strategy is proposed in this paper. It is allowed that there are at mostkmisdiagnosed nodes. In this paper, we determine theg-extra conditional diagnosability of hypercubes and propose sequential-diagnosis algorithms for hypercubes with low time complexities under the Preparata, Metze, and Chien (PMC) model and the MM* model which is a special case of the Maeng and Malek (MM) model. [ABSTRACT FROM PUBLISHER]

This exploratory study focuses on understanding the thematic trends and changes in 1,078 articles published in Human Service Organizations: Management, Leadership, and Governance (HSO) journal. Structural Topic Model (STM) was used to examine how topics have changed over time. Fifteen topics were uncovered, and the most widely studied topic in HSO's 40-year history was gender-related issues. The results show that the prevalence of topics varied over time. While some topics (e.g., "Performance and measurement," "Relationship with the market and public sector," "Planning, implementation, and feedback," and "Social work education") showed decreasing trends, others (e.g., "Network and collaboration," "Board and executive," "Program and evidence," and "Supervision and team") showed increasing trends. This study can contribute to reviewing the past social work management research and may help suggest some projections or directions for managers and researchers in human service organizations. [ABSTRACT FROM AUTHOR]

Identification of high-magnitude heat flux in real time is a challenging problem, since most of the currently available algorithms require large computation time in comparison with the time scale of the real physical problem. This paper presents a methodology that allows for quantifying the unsteady heat flux in real time by using the steady-state Kalman filter. Two different cases have been used to verify this algorithm and the estimates are in excellent agreement with the reference values. [ABSTRACT FROM AUTHOR]

An analytical mathematical model and a branch-and-bound algorithm for single-track cyclic multi-hoist scheduling problems are proposed. The objective is to minimize the cycle time for a given number of hoists. The collision-free single-track constraints are first formulated as disjunctive inequalities. It is then shown that this formulation is a very strict and necessary condition. To be a sufficient and necessary one, two additional properties, like collision-checking rules, must hold in optimal solutions. It is proved that a solution violating these two properties due to their relaxation is always dominated by a collision-free one. Therefore, these two properties are relaxed in the branch-and-bound algorithm. The computation of lower bounds in the branch-and-bound algorithm requires the solution of a specific linear programming problem, which can be solved by using a graph-based polynomial algorithm. Computational results with both benchmark and randomly generated test instances are presented. [ABSTRACT FROM AUTHOR]

This paper investigates the smallest level of buffering (LB), necessary to ensure the desired production rate in serial lines with unreliable machines. The reliability of machines is assumed to obey either exponential, or Erlang, or Rayleigh models. The LB is measured in units of the average downtime, T[sub down]. The dependence of LB on the reliability model, the number of machines, M, the average uptime, T [sub up], and the efficiency, e = T[sub up]/(T[sub up] + T[sub down]) is analysed. It is shown that reliability models with larger coefficient of variation require larger LB, and an empirical law that connects LB of the exponential model with those for other reliability models is established. It is shown that LB is an increasing function of M, but with an exponentially decreasing rate, saturating at around M = 10. Also, it is shown that LB does not depend explicitly on T[sub up] and is a decreasing function of e . Based on these results, rules-of-thumb are provided for selecting buffer capacity, which guarantee sufficiently high line efficiency. [ABSTRACT FROM AUTHOR]

Motivated by the behavioral phenomena that occur while human operators are carrying out tasks, we study multitasking scheduling problems with a rate-modifying activity. In the problems, the processing of a selected task suffers from interruptions by other tasks that are available but unfinished, and the human operators regularly engage rest breaks during work shifts allowing them to recover or mitigate some of the negative effects of fatigue. The objectives are to respectively minimize: makespan, total completion time, maximum lateness, and due-date assignment related cost by determining when to schedule the rate modifying activity and the optimal task sequence in the presence of multitasking. Scheduling models and algorithms are proposed to solve the problems. The numerical examples are presented to illustrate the theorems and algorithms. [ABSTRACT FROM PUBLISHER]

In recent years, there has been a trend in the research community to solve large-scale complex planning and design problems using the modern heuristics optimization techniques (i.e. tabu search, genetic algorithms, etc.). This is mainly due to unsuitability of the classical solution techniques in many circumstances. Depending upon the assumptions made and the modelling approach used, aggregate production planning (APP) problems can be quite complex and large scale. Therefore, there is a need to investigate the suitability of modern heuristics for their solution. In this paper, the multiple-objective APP problem is formulated as a pre-emptive goal-programming model and solved by a specially developed multiple-objective tabu search algorithm. The mathematical formulation is built upon Masud and Hwang's model (original model) due to its extensibility characteristics. The present model extents their model by including subcontracting and setup decisions. The multiple-objective tabu search algorithm is applied to both the original and extended model. Results obtained from the solution of the original model are then compared. It is observed that the multiple-objective tabu search algorithm can be used as an alternative solution mechanism for solving APP problems. During this study, an object-oriented program is also developed using C++. This software is named as MOAPPS 1.0 (Multiple Objective Aggregate Production Planning Software). [ABSTRACT FROM AUTHOR]

Considering the influence of the alternating current side resistor, this paper completes the mathematical model for the three-phase four-leg active power filter and deduces the discrete model of the deadbeat control. A novel delay compensation method is proposed to improve the deadbeat control algorithm. Comparing with the algorithm without delay compensation, the proposed algorithm can effectively reduce the delays caused by digital computing and pulse width modulation output. This is achieved by increasing the sampling and processing frequency without estimating the actual values. The predictive algorithms are also analysed in this paper. For the improved algorithm, the simulation and experimental results show that the total harmonic distortion values of three-phase source currents become lower and the neutral current becomes smaller than the algorithm without delay compensation. Therefore the proposed algorithm can solve the harmonic and unbalancing problems effectively. [ABSTRACT FROM AUTHOR]

Energy optimisation is one of the important issues in the research of wireless sensor networks (WSNs). In the application of monitoring, a large number of sensors are scattered uniformly to cover a collection of points of interest (PoIs) distributed randomly in the monitored area. Since the energy of battery-powered sensor is limited in WSNs, sensors are scheduled to wake up in a large-scale sensor network application. In this paper, we consider how to reduce the energy consumption and prolong the lifetime of WSNs through wake-up scheduling with probabilistic sensing model in the large-scale application of monitoring. To extend the lifetime of sensor network, we need to balance the energy consumption of sensors so that there will not be too much redundant energy in some sensors before the WSN terminates. The detection probability and false alarm probability are taken into consideration to achieve a better performance and reveal the real sensing process which is characterised in the probabilistic sensing model. Data fusion is also introduced to utilise information of sensors so that a PoI in the monitored area may be covered by multiple sensors collaboratively, which will decrease the number of sensors that cover the monitored region. Based on the probabilistic model and data fusion, minimum weight probabilistic coverage problem is formulated in this paper. We also propose a greedy method and modified genetic algorithm based on the greedy method to address the problem. Simulation experiments are conducted to demonstrate the advantages of our proposed algorithms over existing work. [ABSTRACT FROM AUTHOR]

This paper provides a developed mathematical model to derive the optimal integrated lot sizing in a multi-level supply chain with imperfect quality products. The developed mathematical model has a bi-objective function, with conflicting goals, minimizing the chain inventory costs and maximizing the chain total profit aided to find optimum policy for integrated lot sizing. We further actualize the problem by assuming multiple stochastic constraints. The mathematical formulation of the problem is stochastic, nonlinear, and large. In this regard, the interior point algorithm that is developed as more effective algorithm with less iteration is used for solving the recent convex nonlinear model. Numerical example shows that the developed interior point method is an efficient method with excellent performance in terms of the quality of the solution. Also, Sensitivity analysis shows that the developed interior point method is an efficient method with excellent performance in terms of the quality of the solution. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an iteratively reweightedminimization algorithm (IRL1 algorithm) for solving the elasticminimization problem. We prove that any sequence generated by the IRL1 algorithm is bounded and asymptotically regular. We also prove that the sequence is convergent for any rationaland the limit is a stationary point of the elasticminimization problem. Moreover, under certain conditions, we present an error bound between the limit point of convergent sequence and the sparse solution of underdetermined linear system. Numerical experiments on sparse vector recovery are presented to demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Improving tractive effort is a very complex task in locomotive design. It requires the development of not only mechanical systems but also power systems, traction machines and traction algorithms. At the initial design stage, traction algorithms can be verified by means of a simulation approach. A simple single wheelset simulation approach is not sufficient because all locomotive dynamics are not fully taken into consideration. Given that many traction control strategies exist, the best solution is to use more advanced approaches for such studies. This paper describes the modelling of a locomotive with a bogie traction control strategy based on a co-simulation approach in order to deliver more accurate results. The simplified and advanced modelling approaches of a locomotive electric power system are compared in this paper in order to answer a fundamental question. What level of modelling complexity is necessary for the investigation of the dynamic behaviours of a heavy-haul locomotive running under traction? The simulation results obtained provide some recommendations on simulation processes and the further implementation of advanced and simplified modelling approaches. [ABSTRACT FROM AUTHOR]

In recent years, advances in sensor technology, connectedness and computational power have come together to produce huge data-sets. The treatment and analysis of these data-sets is known as big data analytics (BDA), and the somewhat related term data mining. Fields allied to human factors/ergonomics (HFE), e.g. statistics, have developed computational methods to derive meaningful, actionable conclusions from these data bases. This paper examines BDA, often characterised by volume, velocity and variety, giving examples of successful BDA use. This examination provides context by considering examples of using BDA on human data, using BDA in HFE studies, and studies of how people perform BDA. Significant issues for HFE are the reliance of BDA on correlation rather than hypotheses and theory, the ethics of BDA and the use of HFE in data visualisation. Practitioner Summary:Human factors/ergonomics practitioners are increasingly likely to work with the large data bases and novel software associated with big data analytics (BDA) and similar fields such as data mining. This paper shows the characteristics of BDA and details methodological and ethical issues that arise in BDA. [ABSTRACT FROM AUTHOR]

This article develops a hub-and-spoke architecture for a parcel delivery system using a network that includes a distribution centre and several cross-dock facilities. Several real-world assumptions, including an electric truck fleet, mobile charging station, third-party logistics, capacity constraints, last-mile deliveries and customer dissatisfaction, are incorporated in this problem. Besides, because of the high complexity of the problem, a novel matheuristic algorithm based on the combination of the fix-and-relax algorithm (FARA) and genetic algorithm (GA), namely Mb-FARGA, is developed to solve large-sized instances. A comprehensive computational analysis is accomplished to validate the proposed mathematical models and evaluate the performance of the Mb-FARGA method. According to the results, the Mb-FARGA method demonstrates a very favourable performance. Moreover, the results show that considering a distribution centre with appropriate capacity in the cross-docking system is an excellent strategy to enhance customer satisfaction, improve the system's performance and reduce capacity shortages. [ABSTRACT FROM AUTHOR]

In this paper, we show an algorithmic procedure to compute abelian subalgebras and ideals of a given finite-dimensional Leibniz algebra, starting from the non-zero brackets in its law. In order to implement this method, the symbolic computation package MAPLE 12 is used. Moreover, we also show a brief computational study considering both the computing time and the memory used in the two main routines of the implementation. Finally, we determine the maximal dimension of abelian subalgebras and ideals for 3-dimensional Leibniz algebras and 4-dimensional solvable ones over. [ABSTRACT FROM PUBLISHER]

Objective: With the overall goal to harmonize prospective effectiveness assessment of active safety systems, the specific objective of this study is to identify and evaluate sources of variation in virtual precrash simulations and to suggest topics for harmonization resulting in increased comparability and thus trustworthiness of virtual simulation-based prospective effectiveness assessment. Methods: A round-robin assessment of the effectiveness of advanced driver assistance systems was performed using an array of state-of-the-art virtual simulation tools on a set of standard test cases. The results were analyzed to examine reasons for deviations in order to identify and assess aspects that need to be harmonized and standardized. Deviations between results calculated by independent engineering teams using their own tools should be minimized if the research question is precisely formulated regarding input data, models, and postprocessing steps. Results: Two groups of sources of variations were identified; one group (mostly related to the implementation of the system under test) can be eliminated by using a more accurately formulated research question, whereas the other group highlights further harmonization needs because it addresses specific differences in simulation tool setups. Time-to-collision calculations, vehicle dynamics, especially braking behavior, and hit-point position specification were found to be the main sources of variation. Conclusions: The study identified variations that can arise from the use of different simulation setups in assessment of the effectiveness of active safety systems. The research presented is a first of its kind and provides significant input to the overall goal of harmonization by identifying specific items for standardization. Future activities aim at further specification of methods for prospective assessments of the effectiveness of active safety, which will enhance comparability and trustworthiness in this kind of studies and thus contribute to increased traffic safety. [ABSTRACT FROM AUTHOR]

In this paper some aspects of the dynamical behavior of manipulators with non-rigid transmissions between servomotors and links are reported. The dynamical effects related with transmission elasticity are analysed by means of a mathematical model and some dedicated software. The simulation results show how different laws of motion can induce end-effector vibrations, sometimes quite wide caused by occurrence of resonance. These vibrations can be reduced by means of an appropriate computing of the servomotors laws of motion; in this paper an algorithm is described to determine the above-mentioned laws of motions. The authors propose a method to compute servomotors laws of motion that permit to the end-effector to describe a planned trajectory with a robot arm having non rigid transmission between motors and links; this technique just needs the knowledge of a simple manipulator mathematical model and is apart from the control system. This method has been validated using a virtual prototype realized by co-simulations between ADAMS code, for the mechanical model, and SIMULINK code, for the control and actuator systems. [ABSTRACT FROM AUTHOR]

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions. [ABSTRACT FROM AUTHOR]

Mathematical models, in which many input variables are involved, require a range of input and output data, since the number of parameters increases with the input variables. GMDH (Group Method of Data Handling) has been used for the identification of a mathematical model that has many input variables but limited data needs by using a hierarchical structure. This paper proposes a neuro-fuzzy (GMDH model, adopting Gaussian radial basis functions (GRBF) as partial descriptions of GMDH. GRBF is reinterpreted as both a simplified fuzzy reasoning model and as a three-layered neural network. As an example of applying the algorithm, the wheel wear equation is identified, using data from experiments of abrasive cut-off. In the model, characteristics of work materials, grinding fluids, factors of wheels, wheel velocity and table feed are used as input variables, and the grinding ratio is the resulting output. The validity of the model is confirmed within the predicted accuracy by using additional data. [ABSTRACT FROM AUTHOR]

The paper deals with the problem of optimization of a quality inspection process structure. The problem is identified with designing an optimal arrangement of inspection operations in a production process (linkages of the quality inspection process with manufacturing and accessory processes). Three mathematical models for the cases of specialized and versatile inspection stations are formulated. It is shown that the problem can be treated as a particular case of a standard assignment problem. An optimization procedure, grounded on Balas' algorithm, is proposed. A numerical example, based on real data, is given. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to describe a new formulation of the mixed-model sequencing model in such a way as to minimize the risk of stopping the conveyor under the circumstances of system variability and to develop an efficient heuristic method for large-scale, mixed-model assembly lines. The proposed method always produced optimal solutions for randomly constructed small-scale, mixed-model sequencing problems for which the optimal solutions were available through the application of the improved branch and bound method. The method should produce excellent (and almost always optimal) results for actual large-scale, mixed-model sequencing problems. [ABSTRACT FROM AUTHOR]

Consider scheduling n independent, single operation jobs, all available at time zero, on m identical processors. Further, assume that each job must be processed by exactly one of these processors, and it is desired to minimize makespan. This paper reports a computationally efficient procedure for treating this problem, which utilizes human ingenuity to improve on a traditional solution procedure. Computational experience with the procedure indicates that good solutions to large problems are easily obtained; in fact out of 240 test problems, the optimal solution was found in every case. The entire procedure is simple enough for a shop foreman to be able to solve large problems by hand. [ABSTRACT FROM AUTHOR]

This paper presents a new model for handling positional uncertainty in the process of line simplification. It considers that positional uncertainty in a simplified line is caused by (a) positional uncertainty in an initial line propagated through the process and (b) a deviation of the simplified line from the initial line. In order to describe the uncertainty in the simplified line, the maximum distance is defined as a measure. This measure is further adopted to determine parameters to a line simplification algorithm. Therefore, this model makes a step forward in the implementation of an uncertainty indicator for the line simplification. As compared existing models, the proposed uncertainty model in this paper is more comprehensive in uncertainty assessment for line simplification. [ABSTRACT FROM AUTHOR]

This paper presents a time domain technique for estimating dynamic loads acting on a structure from acceleration time response measured experimentally at a finite number of optimally placed accelerometers on the structure. The technique utilizes model reduction to obtain precise load estimates. The structure essentially acts as its own load transducer. The approach is based on the standard equilibrium equations of motion in modal coordinates. The modal parameters of a system – natural frequencies, mode shapes and damping factors – can be estimated experimentally from measured data, analytically for simple problems, or using the finite element method. For measurement of the acceleration response, there can be a large number of locations on the structure where the accelerometers can be mounted, and the precision with which the applied loads are estimated from measured acceleration response may be strongly influenced by the locations selected for accelerometer placements. A solution approach, based on the construction of D-optimal designs, is presented to determine the number and optimum locations of accelerometers that will provide the most precise load estimates. An improvement in the algorithm, based on reduced modal matrix, is further proposed to reconstruct the input forces accurately. Numerical examples that help understand the main characteristics of the proposed approach are also presented. The numerical results illustrate the effectiveness of the proposed technique in accurately recovering the loads imposed on discrete as well as continuous systems. [ABSTRACT FROM AUTHOR]

Recently, we studied communication delay in distributed control of untimed discrete-event systems based on supervisor localisation. We proposed a property called delay-robustness: the overall system behaviour controlled by distributed controllers with communication delay is logically equivalent to its delay-free counterpart. In this paper, we extend our previous work to timed discrete-event systems, in which communication delays are counted by a special clock eventtick. First, we propose a timed channel model and define timed delay-robustness; for the latter, a verification procedure is presented. Next, if the delay-robust property does not hold, we introduceboundeddelay-robustness, and present an algorithm to compute themaximaldelay bound (measured by number ofticks) for transmitting a channelled event. Finally, we demonstrate delay-robustness on the example of an under-load tap-changing transformer. [ABSTRACT FROM AUTHOR]

A key agenda of policy-makers in both the developing and the developed worlds is to have an inclusive growth. Financial services have been recognised as one of the fundamental services that have the potential to achieve this objective and help move towards a more just and equitable society. This paper attempts to assess the impact of three information and communication technology-driven initiatives in the field of financial services by differentiating them on the basis of service design. This study goes beyond the stated objective of these services and uses Sen’s capability perspective to study their impact across three non-economic outcome variables viz. literacy, service-specific well-being and empowerment. The data for the study are collected from the urban poor across different locations in a large metropolitan city in South India where the three different services are being offered. The study follows a quasi-experimental design (field study) and ensures matching of the treatment and control groups through propensity score matching. The matched data are analysed using an independent samplet-test. The result of the analysis shows that service design plays a key role in increasing service literacy, improving service-specific well-being and empowering end users. The study suggests that the true challenge for providers (government and partner agencies) of these services is in designing a service that ensures a balance of structure and flexibility without constraining the choice of end users through innovative service blueprints. [ABSTRACT FROM AUTHOR]

In this paper, we discuss the Krylov subspace-based model order reduction methods of second-order systems with time delays, and present two structure-preserving methods for model order reduction of these second-order systems, which avoid to convert the second-order systems into first-order ones. One method is based on a Krylov subspace by using the Taylor series expansion, the other method is based on the Laguerre series expansion. These two methods are used in the multi-order Arnoldi algorithm to construct the projection matrices. The resulting reduced models can not only preserve the structure of the original systems, but also can match a certain number of approximate moments or Laguerre expansion coefficients. The effectiveness of the proposed methods is demonstrated by two numerical examples. [ABSTRACT FROM AUTHOR]

This paper discusses the problem at assigning facilities to locations. Several optimal and sub-optimal-yielding algorithms are discussed mentioning their desirable and undesirable features. A new heuristic algorithm is proposed. The proposed algorithm, combining features from other well known models, and programmed in Fortran IV is tested against existing methods. The results show that the algorithm is efficient, easy to run and is very competitive with other well-known methods. [ABSTRACT FROM AUTHOR]

Mathematicians have long amused themselves with very difficult problems that are treated as puzzles. One of the more recent of these is the travelling-salesman problem. During last two decades several methods have been developed for solving the travelling-salesman problem, which is akin to many other important problems. The problem of determining a manufacturing schedule, when a number of products are to be manufactured over a production facility, is identical to the travelling-salesman problem. This paper discusses a simple approach to the solution of such production scheduling problems. [ABSTRACT FROM AUTHOR]

The article presents a note on a multigoal heuristic for facilities design problem. In their paper, researchers K.N. Dutta and S. Sahu (D+S) give a mathematical model for the multigoal facility design problem. However, the same model had already been developed by researcher M.J. Rosenblatt in 1979 and appeared in the list of references of D+S. The sixteen equations developed for this model in 1982 correspond, one by one, to equations presented by Rosenblatt in 1979. It is quite puzzling that D + S did not mention this fact throughout their text. Furthermore, in a footnote D+S claim that the objective function derived was not correct. It is the intention of this note to show the reader that except for a small typographical error this formulation is correct and it is astonishing that D+S did not realize it. Furthermore, after developing the model, D+S develop a pair wise exchange algorithm. However, this algorithm and its attached flowchart have appeared in different variations in several papers and books. Finally, D+S stated that in their proposed method "only if the department share common boundaries are their closeness ratings added to get the score for a particular assignment."

Machine Learning (ML) can improve the analysis of complex and interrelated factors that place adherent people at risk of viral rebound. Our aim was to build ML model to predict RNA viral rebound from medication adherence and clinical data. Patients were followed up at the Swiss interprofessional medication adherence program (IMAP). Sociodemographic and clinical variables were retrieved from the Swiss HIV Cohort Study (SHCS). Daily electronic medication adherence between 2008–2016 were analyzed retrospectively. Predictor variables included: RNA viral load (VL), CD4 count, duration of ART, and adherence. Random Forest, was used with 10 fold cross validation to predict the RNA class for each data observation. Classification accuracy metrics were calculated for each of the 10-fold cross validation holdout datasets. The values for each range from 0 to 1 (better accuracy). 383 HIV+ patients, 56% male, 52% white, median (Q1, Q3): age 43 (36, 50), duration of electronic monitoring of adherence 564 (200, 1333) days, CD4 count 406 (209, 533) cells/mm3, time since HIV diagnosis was 8.4 (4, 13.5) years, were included. Average model classification accuracy metrics (AUC and F1) for RNA VL were 0.6465 and 0.7772, respectively. In conclusion, combining adherence with other clinical predictors improve predictions of RNA. [ABSTRACT FROM AUTHOR]

This paper is concerned with designing fault detection filters for networked control systems subject to limited communication capacity and a class of sensor stuck faults. By taking into account the communication limitations (e.g. measurement quantisation, signal transmission delays and data packet dropouts) and all possible sensor stuck faults, a unified mathematical model is first presented. Based on this framework, a full-order fault detection filter is designed such that the residual system is asymptotically stable with the prescribed attenuation level in the generalisedH∞sense. In order to further improve the detection performance, an optimisation algorithm is proposed to minimise the threshold. Finally, a spring-mass-damper system is utilised to show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

LetAbe a commutative noetherian ring, and 𝔞 an ideal in it. In this paper we continue the study, begun in [11], of the derived 𝔞-adic completion and the derived 𝔞-torsion functors. Here are our results: (1) a structural characterization of bounded abovecohomologically complete complexes; (2) theCohomologically Complete Nakayama Theorem; and (3) a characterization ofcohomologically cofinite complexes. [ABSTRACT FROM AUTHOR]

Full-cost inventory models are mostly studied in the literature, whereas service level constraints are more common to be observed in practical settings. In this paper, we consider periodic review inventory systems with service level restrictions. The control of such inventory systems is limited to (s, S)-type policies in the literature. To the best of our knowledge, we are the first authors to compare such policies with optimal replenishment policies, and illustrate an average cost difference of 0.64%. This justifies the use of these popular (s, S) policies in practice. Furthermore, we propose a new one-dimensional search procedure that is bounded to set the reorder level s and order-up-to level S, whereas the solution space is unbounded and two dimensional. Our heuristic procedure is guaranteed to satisfy the service level constraint and numerical experiments illustrate that it results in an average cost deviation of 1-2% compared with the best (s, S) policy. Consequently, it significantly outperforms all existing procedures from literature, both in service and costs. [ABSTRACT FROM AUTHOR]

In this paper we introduce an extension of the proximal point algorithm proposed by Güler for solving convex minimization problems. This extension is obtained by substituting the usual quadratic proximal term by a class of convex nonquadratic entropy-like distances, called f-divergences. A study of the convergence rate of this new proximal point method under mild assumptions is given, and further it is shown that this estimate rate is better than the available one of proximal-like methods. Some applications are given concerning general convex minimizations, linearly constrained convex programs and variationnal inequalities. [ABSTRACT FROM AUTHOR]

In this study, we proposed an optimal algorithm for the pallet-loading problem (PLP). The PLP involves determining a loading pattern that can load the most identical boxes with rectangular shapes onto a large rectangular pallet. A new branch and bound algorithm, including a sub-algorithm that cheques the feasibility of the solutions, was proposed to solve a relaxed mathematical model, which did not consider the exact position of the boxes. Because the algorithm constructed the layout row-by-row and used effective branching strategies and improved bounds, it found a solution very quickly. Whenever a solution was obtained for the relaxed problem, another branch and bound algorithm (as a sub-algorithm) was used to check whether the solution obtained was feasible and to determine the resulting layout. The branching strategies in the sub-algorithm used the solution from the relaxation problem to quickly find the layout of the solution. The computational results demonstrated the superiority of the proposed algorithm. The algorithm proposed in this study solved all three million problems presented with an area ratio bound of less than 101 boxes in a minute, except for one. Solutions to all of the problems were obtained within 90 s, while other existing exact algorithms required more than an hour for some problems. [ABSTRACT FROM PUBLISHER]

Minimising earliness and tardiness penalties as well as maximum completion time (makespan) simultaneously on unrelated parallel machines is tackled in this research. Jobs are sequence-dependent set-up times and due dates are distinct. Since the machines are unrelated, jobs processing time/cost on different machines may vary, i.e. each job could be processed at different processing times with regard to other machines. A mathematical model which minimises the mentioned objective is proposed which is solved optimally via lingo in small-sized cases. An intelligent water drop (IWD) algorithm, as a new swarm-based nature-inspired optimisation one, is also adopted to solve this multi-criteria problem. The IDW algorithm is inspired from natural rivers. A set of good paths among plenty of possible paths could be found via a natural river in its ways from the starting place (source) to the destination which results in eventually finding a very good path to their destination. A comprehensive computational and statistical analysis is conducted to analyse the algorithms’ performances. Experimental results reveal that the proposed hybrid IWD algorithm is a trustable and proficient one in finding very good solutions, since it is already proved that the IWD algorithm has the property of the convergence in value. [ABSTRACT FROM PUBLISHER]

The multi-objective reentrant hybrid flowshop scheduling problem (RHFSP) exhibits significance in many industrial applications, but appears under-studied in the literature. In this study, an iterated Pareto greedy (IPG) algorithm is proposed to solve a RHFSP with the bi-objective of minimising makespan and total tardiness. The performance of the proposed IPG algorithm is evaluated by comparing its solutions to existing meta-heuristic algorithms on the same benchmark problem set. Experimental results show that the proposed IPG algorithm significantly outperforms the best available algorithms in terms of the convergence to optimal solutions, the diversity of solutions and the dominance of solutions. The statistical analysis manifestly shows that the proposed IPG algorithm can serve as a new benchmark approach for future research on this extremely challenging scheduling problem. [ABSTRACT FROM PUBLISHER]

In this paper we develop a closed-form and thus computationally highly efficient formula to approximate the value of fixed-rate mortgage-backed securities (MBS). Our modelling framework is based on reduced-form and prepayment-risk-neutral valuation techniques and offers two major extensions compared with existing closed-form approximation approaches: we include a stochastic baseline prepayment factor in our model and we are able to capture the usual S-shaped curve of the refinancing incentive by a piecewise linear approximation. We apply our model to GNMA pass-through securities and test it on a 10-year sample of monthly GNMA MBS market prices for a wide range of coupons. [ABSTRACT FROM AUTHOR]

A number of mortgage prepayment models require a specification of the mortgage rate process. Usually, ad-hoc models are used (e.g., a Treasury yield plus some constant). Recently, a number of papers have appeared where the authors have utilized a mortgage rate implied by the current yield curve (the so-called endogenous mortgage rate). However, the existing computational algorithms suffer from the curse of dimensionality and, consequently, are problematic to use for full-scale problems. A computational algorithm, proposed in this paper, is tractable in the sense that its complexity is equivalent to the problem of mortgage valuation. Moreover, the algorithm does not require iterations. The numerical example is based on a PDE computation. An implementation of a Monte Carlo method is also discussed. [ABSTRACT FROM AUTHOR]

In this paper, a fully fledged optimal power flow (OPF) algorithm with flexible AC transmission systems (FACTS) devices has been developed and presented aiming at the advancement of how FACTS equipment impacts on the security and economy of the wider power network. The proposed modelling uses Newton's method along with Lagrangian multipliers, leading to an efficient algorithm that can handle practical power networks independence of initial settings of FACT controllers parameters. Newton's method provides a suitable vehicle for incorporating the newly developed nonlinear, linearized FACTS models. In this paper, mainly a firing angle-based thyristor controlled series compensators (TCSC) model, a coordinated twovoltage source unified power flow controller (UPFC) model have been developed and presented in details and can easily be extended to other modern FACTS devices such as interline power flow controller (IPFC) and generalized unified power flow controller (GUPFC). The proposed model has capability of converting multi-objective functions into single objective and also can be extended to multiple multi-type FACTS devices. The performance of the proposed model has been validated for IEEE 30 bus system and the solutions so obtained are presented in detail. [ABSTRACT FROM AUTHOR]

The hole-free triangular mesh model is a prerequisite for many applications. In this paper, we propose a novel hole-filling algorithm for triangular meshes in engineering which can recover the geometric features of the original meshes. Firstly, the sharp vertices around the hole are extracted and classified into different feature sets. Then the sharp vertex sets are used to construct feature curves with missing parts in the hole by cubic spline interpolation. These feature curves divide the original complex hole into small, flatter sub-holes. Finally, each sub-hole is triangulated into a set of new triangles, and a series of iterative modifications are employed to refine and improve the geometry of hole according to the properties of surrounding mesh. Experimental results demonstrate that the proposed algorithm is powerful enough to recover the missing shape, and the resulted patching meshes interpolate the shape and density of the surrounding mesh and naturally blend with it, which are of good quality for engineering. [ABSTRACT FROM PUBLISHER]