A New Frequency Analysis Operator for Population Improvement in Genetic Algorithms to Solve the Job Shop Scheduling Problem

Job Shop Scheduling is currently one of the most addressed planning and scheduling optimization problems in the field. Due to its complexity, as it belongs to the NP-Hard class of problems, meta-heuristics are one of the most commonly used approaches in its resolution, with Genetic Algorithms being one of the most effective methods in this category. However, it is well known that this meta-heuristic is affected by phenomena that worsen the quality of its population, such as premature convergence and population concentration in regions of local optima. To circumvent these difficulties, we propose, in this work, the use of a guidance operator responsible for modifying ill-adapted individuals using genetic material from well-adapted individuals. We also propose, in this paper, a new method of determining the genetic quality of individuals using genetic frequency analysis. Our method is evaluated over a wide range of modern GAs and considers two case studies defined by well-established JSSP benchmarks in the literature. The results show that the use of the proposed operator assists in managing individuals with poor fitness values, which improves the population quality of the algorithms and, consequently, leads to obtaining better results in the solution of JSSP instances. Finally, the use of the proposed operator in the most elaborate GA-like method in the literature was able to reduce its mean relative error from 1.395% to 0.755%, representing an improvement of 45.88%.

Direct current geared motor data: Voltage, current, and speed measured under different experimental conditions

This data article describes eleven datasets collected from laboratory individual tests with two DC motors of the same model. The motors are proposed to be used as the actuators of an Automated Guided Vehicle (AGV). Each dataset shares the same structure, with the measurement of twelve variables: instant of measurement, encoder pulse counts, calculated motor velocity, raw current, calculated current, raw voltage from output A1, raw voltage from output B1, calculated voltage from output A1, calculated voltage from output B1, potential difference applied to the motor terminals, motor status, and the Arduino analog output value in pulse width modulation (PWM). The data are helpful to model and identify the system considering its dynamics. Such consideration on control systems design, specifically on AGV position control, can improve the controller accuracy. It also can be useful to study robot design, and mobile robot and AGV simulation.

A New Local Search Adaptive Genetic Algorithm for the Pseudo-Coloring Problem

Several applications result in a gray level image partitioned into different regions of interest. However, the human brain has difficulty in recognizing many levels of gray. In some cases, this problem is alleviated with the attribution of artificial colors to these regions, thus configuring an application in the area of visualization and graphic processing responsible for categorizing samples using colors. However, the task of making a set of distinct colors for these regions stand out is a problem of the NP-hard class, known as the pseudo-coloring problem (PsCP). In this work, it is proposed to use the well-known meta-heuristic Genetic Algorithm together with operators specialized in the local search for solutions as well as self-adjusting operators responsible for guiding the parameterization of the technique during the resolution of PsCPs. The proposed methodology was evaluated in two different scenarios of color assignment, having obtained the best results in comparison to the techniques that configure the state of the art.

A Qualitative Analysis of a USB Camera for AGV Control

The increasing use of Automated Guided Vehicles (AGV) in the industry points to a search for better techniques and technologies to adapt to market requirements. Proper position control and movement give an AGV greater movement accuracy and greater lateral oscillations stability and vibration. It leads to smaller corridors and leaner plants, to more relaxed shipment devices, and to greater safety in the transport of fragile loads, for instance. AGV control techniques are not new, but new sensors’ applications are possible, such as USB cameras. In this sense, it is necessary to ensure the sensor is adequate to control system requirements. This work addresses AGVs driven by passive floor demarcations. It presents a qualitative analysis of a USB camera as sensors for AGV control, not yet a common industrial application. We performed the experiments with a small AGV prototype on an eight-shaped lane, varying both camera parameters and AGV parameters, such as linear speed. The AGV uses a USB camera with different image processing settings—different morphological filters structuring elements shapes and sizes, and three different image resolutions—to analyze the factors that affect line detection and control processing. This paper’s main contribution is a qualitative and quantitative analysis for the different sensor configurations. In addition, it discusses the influence sources on camera image as a position sensor. Furthermore, the experiments confirm sensor pertinence for the proposed control system.