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Number of results: 5
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Abstract

This paper presents a model of scheduling of multi unit construction project based on an NP-hard permutation flow shop problem, in which the considered criterion is the sum of the costs of the works' execution of the project considering the time of the project as a constraint. It is also assumed that each job in the units constituting the project may be realized in up to three different ways with specific time and cost of execution. The optimization task relies on solving the problem with two different decision variables: the order of execution of units (permutation) and a set of ways to carry out the works in units. The task presented in the paper is performed with the use of a created algorithm which searches the space of solutions in which metaheuristic simulated annealing algorithm is used. The paper presents a calculation example showing the applicability of the model in the optimization of sub-contractors' work in the construction project.
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Abstract

The paper is an exploration of the optimal design parameters of a space-constrained electromagnetic vibration-based generator. An electromagnetic energy harvester is composed of a coiled polyoxymethylen circular shell, a cylindrical NdFeB magnet, and a pair of helical springs. The magnet is vertically confined between the helical springs that serve as a vibrator. The electrical power connected to the coil is actuated when the energy harvester is vibrated by an external force causing the vibrator to periodically move through the coil. The primary factors of the electrical power generated from the energy harvester include a magnet, a spring, a coil, an excited frequency, an excited amplitude, and a design space. In order to obtain maximal electrical power during the excitation period, it is necessary to set the system’s natural frequency equal to the external forcing frequency. There are ten design factors of the energy harvester including the magnet diameter (Dm), the magnet height (Hm), the system damping ratio (ζsys), the spring diameter (Ds), the diameter of the spring wire (ds), the spring length (ℓs), the pitch of the spring (ps), the spring’s number of revolutions (Ns), the coil diameter (Dc), the diameter of the coil wire (dc), and the coil’s number of revolutions (Nc). Because of the mutual effects of the above factors, searching for the appropriate design parameters within a constrained space is complicated. Concerning their geometric allocation, the above ten design parameters are reduced to four (Dm, Hm, ζsys, and Nc). In order to search for optimal electrical power, the objective function of the electrical power is maximized by adjusting the four design parameters (Dm, Hm, ζsys, and Nc) via the simulated annealing method. Consequently, the optimal design parameters of Dm, Hm, ζsys, and Nc that produce maximum electrical power for an electromagnetic energy harvester are found.
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Abstract

This paper presents methods for optimal test frequencies search with the use of heuristic approaches. It includes a short summary of the analogue circuits fault diagnosis and brief introductions to the soft computing techniques like evolutionary computation and the fuzzy set theory. The reduction of both, test time and signal complexity are the main goals of developed methods. At the before test stage, a heuristic engine is applied for the principal frequency search. The methods produce a frequency set which can be used in the SBT diagnosis procedure. At the after test stage, only a few frequencies can be assembled instead of full amplitude response characteristic. There are ambiguity sets provided to avoid a fault tolerance masking effect.
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