Nikica Hlupic

Why (not) ORM

The two widely used approaches to data modelling, the application of Unified Modelling Language (UML) and Object Role Modelling (ORM) are compared. Since one of the purposes of modelling is to present and clarify the system design, the key comparison criteria were expressivity, i.e., clear presentation and easy perception of the stored information and substantiality, i.e., ability to store lots of information. A few characteristic situations were chosen that frequently arise in data modelling practice, and the examples clearly show how the same information can be very differently perceptive in ORM and UML models. Thus, the paper can help in selection of the modelling framework for a particular project

Simulation library for Resource Constrained Project Scheduling with uncertain activity durations

Stochastic Resource Constrained Project Scheduling (SRCPS) is among the hardest combinatorial problems. Exact calculations of interesting measures, such as expected project duration and the probability of satisfying the deadline, using known probabilities are in #P even for relaxed instances of the problem where resource constraints are ignored. The most common approach is to use substantial simulation to evaluate candidate solutions. All of the work so far uses ad-hoc developed simulation environments with prevalent use of a priori generated activity duration scenarios. This paper describes the discrete-time simulation library aimed to support the creation of simulation-based algorithms for solving SRCPS problems with known probability distributions of activity durations. The library is designed, in the first instance, with shared memory parallelization of simulation, using OpenMP. Runtime parallelized generation of random activity duration scenarios is supported and we deal with “inconveniences” that are otherwise elegantly avoided using a priori generated activity duration scenarios. However, in some approaches that is not feasible and runtime scenario generation has to be used. We propose modular organization of simulators that enables better reuse of basic intrinsic project scheduling functionality.

Improved frequency measurement by means of DMM and verification of its specifications

A simple, but highly accurate, sampling method for the measurement of frequency by means of a digital multimeter (DMM) or a digital voltmeter (DVM) is explained both theoretically and from the applicative point of view. The mathematical background is given in short form, and comparison with other solutions is provided. High accuracy and behavior regarding random errors are foreseen by computer simulation and then proved in real laboratory measurements. Finally, verification of factory time-base specifications of sophisticated equipment is shown taking an HP 3458A DMM as an example device under test.

Cloud-distributed computational experiments for combinatorial optimization

The development of optimization algorithms for combinatorial problems is a complicated process, both guided and validated by the computational experiments over the different scenarios. Since the number of experiments can be very large and each experiment can take substantial execution time, distributing the load over the cloud speeds up the whole process significantly. In this paper we present the system used for experimental validation and comparison of stochastic combinatorial optimization algorithms, applied in the specific case of project scheduling problems.

A Few Notes on Variance of Frequency Estimated Applying Analytical Leakage Compensation

One of the most accurate and commonly accepted methods for spectral analysis, i.e., estimation of frequency from samples of a signal, is analytical leakage compensation, briefly called analytical solution (AS). The AS estimate is negligibly biased, but it is the whole class of solutions whose variance depends on a free parameter named K. Thus, an important step in AS algorithm is calculation of optimal Kopt, which selects the minimum variance solution from theoretically infinite set. The original paper provides complete set of needed formulae, and here a few other relations are discussed, which can be used to further reduce the variance, if properly applied according to the specified criterion.

Planning horizons based proactive rescheduling for stochastic resource-constrained project scheduling problems

Abstract Parties that collaborate on projects need to synchronize their efforts. For this reason they seek a decreased rescheduling variability of the time arrangements. Proactive–reactive scheduling is important in such situations. It predominantly achieves synchronization through a shared baseline schedule and deviation penalties. As the latter currently introduce an unrealistically high level of inflexibility, the solution methods never proactively update the baseline schedule. We propose threshold-based cost functions for the deviation penalties to enable a more realistic modeling of aspects of project collaboration. These functions introduce a greater degree of flexibility through the notion of planning horizons for the activities. This results in the possibility of profitable proactive changes to the baseline schedule. We present two metaheuristic approaches for the case of stochastic durations: rollout-based and iterative policy search. Both these approaches use such opportunities to achieve substantial cost–performance improvements in comparison to the best existing method. This enhancement comes at the price of an increased computational burden and the greater complexity of the solution space.

Computational Aspects of Efficient Estimation of Harmonically Related Sine-Waves

This paper proposes an actual implementation of a well-known method [1] for spectral analysis of signals composed of harmonically related sine waves. The method itself requires computations which carried out directly according to the theoretical formulas do not yield computationally efficient implementation. Thus, utilizing matrix factorizations and mathematical “shortcuts”, several algorithms have been developed, which perform computations efficiently and make the method suitable for large-scale applications. Implementation details are clearly explained both theoretically and from computational point of view, and the achieved improvements have been proven by extensive simulations. Particular calculations applied will be equally efficient in all similar problems, which renders the proposed routines into widely useful building blocks.

Mark without much Sweep Algorithm for Garbage Collection

In this paper two simple improvements over traditional mark-sweep collector are proposed. The core idea is placing small objects of the same type in buckets. The buckets are organised in such way to eliminate the internal fragmentation, sweeping, and freeing inside them. The measured improvement of garbage collection time over traditional mark-sweep is 19%. Another proposed improvement is more general and is applicable to other garbage collection algorithms as well. It uses heuristics to control the heap growth. The regularities in behaviour of objects of particular types are used to determine whether the collection should be performed or avoided in favour of immediate heap expansion. The heap expansion algorithm reduces garbage collection time over traditional mark-sweep for 49% while keeping the heap size approximately the same.

A Note on Optimality of Analytical Leakage Compensation at Boundary Frequencies

The interpolated fast Fourier transform (IFFT) was one of the first methods for the highly accurate estimation of sine wave parameters, and its first successful descendant was analytical leakage compensation [which is commonly called analytical solution (AS)]. The AS estimate of frequency is a whole class of solutions whose variance depends on a free parameter K. Thus, to extract the minimum variance solution from a theoretically infinite set, we have to find the optimal value K opt. This paper clarifies the mathematical background of AS and proposes two new solutions for K opt, which reduce the variance of AS estimates of low and high frequencies close to an integer. All inferences are justified by simulations, which confirm the validity of theoretical considerations.

Sampling Capabilities of a DMM - Determination of Key Parameters

A sampling method for indirect measurement of all relevant parameters of sampling device is presented. One can determine sampling frequency inaccuracy, integration interval inaccuracy and latency time. All these parameters can be determined with relative error less than 10 ppm, except latency time whose absolute accuracy is about 60 ns