The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper deals with the Job Shop Scheduling Problem (JSP) with the objective of minimizing the makespan criterion, the time elapsed between the start of the first job and end of the last job arranged in a job sequence. We propose a novel multi-population based framework called HADP-JSP to solve the JSP. In the HADP-JSP the main population is divided into several groups. Each group adaptively chooses...
The goal of this paper is to present a comparison among three known metaheuristics: Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). For the comparison, the design of an LC - Voltage Controlled Oscillator (LC-VCO) is considered, where the minimization of both VCO phase noise and power consumption is envisaged. The objective of this comparison is to find the algorithm...
An efficient and reliable evolutionary based meta-heuristic approach, termed as simulated annealing, is presented for the solution of optimal economic power dispatch. The generation of electricity from the fossil fuel releases several contaminants, such as sulphur oxides, nitrogen oxides and carbon dioxide, into the atmosphere. Simulated annealing algorithmic approach to power system optimization,...
The goal of our data-mining multi-agent system is to facilitate data-mining experiments without the necessary knowledge of the most suitable machine learning method and its parameters to the data. In order to replace the expertâs knowledge, the meta-learning subsystems are proposed including the parameter-space search and method recommendation based on previous experiments. In this paper...
Combined the characteristic of simulated annealing, we propose a multi-objective genetic algorithm based on simulated annealing. We take the advantage of simulated annealing, improve the traditional multi-objective genetic algorithm, and avoid the premature convergence of the algorithm. Experimental results show that the improved algorithm improve the solution efficiency of the traditional multi-objective...
This paper reports on an initial attempt to solve the nurse rostering problem using an evolutionary algorithm selection perturbative hyper-heuristic. The main aim of this study is to get a feel for the potential of such a hyper-heuristic in solving the nurse rostering problem. This will be used to direct future extensions of this work. This study identifies low-level perturbative heuristics for this...
This paper presents a metaheuristic optimization-based approach to mobile robot path planning problem. A comparative study between trajectory-based metaheuristic optimization and population-based metaheuristic optimization is conducted. Breadth-first deterministic search is used to find the optimal solution (ground truth) that is compared to the paths generated by tabu search, simulated annealing...
The so-called heuristics have been widely used in solving combinatorial optimization problems because they provide a simple but effective way to find an approximate solution. These technologies are very useful for users who do not need the exact solution but who care very much about the response time. For every existing heuristic algorithm has its pros and cons, a hyper-heuristic clustering algorithm...
Data compression is very important today and it will be even more important in the future. Textual data use only limited alphabet - total number of used symbols (letters, numbers, diacritics, dots, spaces, etc.). In most languages, letters are joined into syllables and words. All three approaches are useful in text compression, but none of them is the best for any file. This paper describes a variant...
This paper presents binary particle swarm optimization (BPSO) for finding an optimum conflict-free transmission schedule for a broadcast radio network. This is known as Broadcast Scheduling Problem (BSP) and shown as an NP-complete problem in earlier studies. Because of this NP-complete nature, earlier studies used genetic algorithms, mean field annealing, neural networks, factor graph and sum product...
General compression algorithms were designed for usage characters as basic symbols. Later, algorithm which used words were developed. The problem is that there is no clear line which defines if is better to use characters or words. In this paper, we developed optimization algorithm based on simulated annealing that selects only several words from all possible words and combine them with character...
Quadratic assignment problem (QAP) is a hard and classical combinatorial optimization problem. Simulated annealing algorithm has been successfully applied to solve QAP. However, the search of simulated annealing algorithm might usually get stuck with local optima due to the low acceptable moves, particularly when the barrier is high and the temperature is low. In this paper, we propose a tabu-based...
Node localization in wireless sensor networks (WSNs) is important for applications such as military surveillance, environmental monitoring, robotics, and many others. The sensor motes used in this type of application present low-power and low-cost profile. Hence, they require methods that compute their positions using indirect information such as Received Signal Strength Indicator (RSSI). This work...
This study looks at the system availability optimization problem under different resource and design configuration constraints by applying Tabu-GA combination method. From the point of view of logistics engineering, availability optimization applied in the initial system development period, plays a key role to affect system reliability, system maintenance planning, logistics requirements, and related...
This paper brings out the studies of generation scheduling problem in an electrical power system. This paper presents some general reviews of research and developments in the field of unit commitment based on published articles and web-sites. Here, it is set about to perform a comprehensive survey of research work made in the domain of Unit Commitment using various techniques. This may be a helpful...
In this study, a nonlinear forecasting model is proposed in order to obtain accurate prediction results and ameliorate forecasting performances. In the model, the genetic algorithm (GA) is coupled with simulated annealing (SA) algorithms to evolve a back-propagation neural network (BPNN) algorithm, called GASANN. The new model's performance is compared with three individual forecasting models, namely...
Due to the critical blood shortages in South Africa and around the world, the assignment of blood can be considered an important real world optimization problem. This paper presents a mathematical model that facilitates good management and assignment of red blood cell units in order to minimize the quantity of imported units from outside the system. The model makes use of the Multiple Knapsack Algorithm,...
The availability of different flavor of processor architecture coupled with computer codes of various nature poses a discreet challenge to the programmers in forms of code optimization. Programmers need to contemplate on optimization during pre and post implementation to take advantage of the hardware given for a specific nature of the code. To compliment this requirement, the evolution of compiler...
The authors examine optimization of the antenna array beamformer bank for a technique to apply coherent signal subspace processing in the beam-space of a bank of true time delay beamformers. This technique offers computational expense advantages over element-space methods, Mean Square Error (MSE) performance similar to wideband coherent subspace techniques and is frequency invariant. This article...
In this paper, we deal with a preventive maintenance (PM) scheduling and spare parts problems for a rolling stock system. We determine the optimal PM interval and the optimal number of spare parts for components in the rolling stock system to minimize the system life cycle cost during satisfying the system target availability. The system availability and system life cycle cost are estimated by simulation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.