The planning problem can be solved with a large variety of different approaches, and a significant amount of work has been devoted to the automation of planning processes using different kinds of methods. This paper focuses on the use of specific local search algorithms for real-world production planning based on experiments with real-world data, and presents an adapted local search guided by evolutionary metaheuristics. To make algorithms efficient, many specifics need to be considered and included in the problem solving. We demonstrate that the use of specialized local searches can significantly improve the convergence and efficiency of the algorithm. The paper also includes an experimental study of the efficiency of two memetic algorithms, and presents a real-world software implementation for the production planning.
COBISS.SI-ID: 24911399
The application of SRAM-based field-programmable gate arrays (FPGAs) in mission-critical systems requires error mitigation and recovery techniques to protect them from the errors caused by high-energy radiation, also known as single event upsets (SEUs). For this, modular redundancy and runtime partial reconfiguration are commonly employed techniques. However, the reported solutions feature different tradeoffs in the area overhead and the fault latency. In this paper,we propose a lowarea-overhead SEU recovery mechanism and describe its application in different self-recoverable architectures, which are experimentally evaluated using a specially designed fault-emulation environment. The environment enables the user to inject faults at selected locations of the configuration memory and experimentally evaluate the reliability of the developed solutions.
COBISS.SI-ID: 26122535
This paper presents an ACO-based algorithm for numerical optimization capable of solving high-dimensional real-parameter optimization problems. The algorithm, called the Differential Ant-Stigmergy Algorithm (DASA), transforms a real-parameter optimization problem into a graph-search problem. We show that the DASA is a competitive continuous optimization algorithm that solves high-dimensional problems effectively and efficiently.
COBISS.SI-ID: 23618855
This paper presents the design of a wireless pressure-monitoring system for harsh-environment applications. Two types of ceramic pressure sensors made with a low-temperature cofired ceramic (LTCC) were considered. The first type is a piezoresistive strain gauge pressure sensor. The second type is a capacitive pressure sensor, which is based on changes of the capacitance values between two electrodes: one electrode is fixed and the other is movable under an applied pressure. The design was primarily focused on low power consumption. Reliable operation in the presence of disturbances, like electromagnetic interference, parasitic capacitances, etc., proved to be contradictory constraints. A piezoresistive ceramic pressure sensor with a high bridge impedance was chosen for use in a wireless pressure-monitoring system. The described solution allows for the integration of a sensor element with an energy harvester in a single substrate packaged inside a compact housing.
COBISS.SI-ID: 25475367
This paper presents a solution in which a wireless interface is employed to replace the cables in bridge-sensor measurement applications. The most noticeable feature of the presented approach is the fact that the wireless interface simply replaces the cables without any additional hardware modification to the existing system. In this approach, the concept of reciprocal topology is employed, where the transmitter side acquires signals with its own transfer function and the receiver side reconstructs them with the transfer function reciprocal to the transmitter transfer function. In this paper the principle of data acquisition and reconstruction is described together with the implementation details of the signal transfer from the sensor to the signal-monitoring equipment. The wireless data communication was investigated and proprietary data-reduction methods were developed. The proposed methods and algorithms were implemented using two different wireless technologies. The performance was evaluated with a dedicated data-acquisition system and finally, the test results were analyzed. The two different sets of results indicated the high level of amplitude and the temporal accuracy of the wirelessly transferred sensor signals.
COBISS.SI-ID: 26024231