Swarm intelligence algorithms

Chez nos anciens et dans les sociétés traditionnelles pour faire passer un message, il était souvent fait usage du conte. Par l'image qu'il évoque en nous, et que la parole fait entrer en résonance, il peut nous éclairer beaucoup plus qu'un long discours théorique. Celui qui va suivre va m'aider à mettre des mots sur mon expérience professionnelle en PMI dans l'accompagnement des familles et la mise en place d'un travail en réseau pluridisciplinaire. Marie-Agnès Jeune Le médecin de PMI et les « psy » Il était une fois une modeste petite ville de banlieue… Au coeur de grandes cités HLM se dresse un espace clair et vitré, visible de très loin, nous pourrions l'appeler un auditorium. Dans ce lieu vivaient des instruments de musique. Chacun jouait sa partition, s'essayant à quelques duos ou trios, mais sur de brèves oeuvres, ils travaillaient surtout la musique du corps. Un peu plus loin dans la ville et dans les communes environnantes, vivaient d'autres orchestres, très spécialisés. Certains connaissaient bien la musique de l'esprit et du coeur, d'autres celle du social, d'autres celle de l'école ou de la crèche… Mais ils se fréquentaient peu.

Chez nos anciens et dans les sociétés traditionnelles pour faire passer un message, il était souvent fait usage du conte. Par l'image qu'il évoque en nous, et que la parole fait entrer en résonance, il peut nous éclairer beaucoup plus qu'un long discours théorique. Celui qui va suivre va m'aider à mettre des mots sur mon expérience professionnelle en PMI dans l'accompagnement des familles et la mise en place d'un travail en réseau pluridisciplinaire. Marie-Agnès Jeune Le médecin de PMI et les « psy » Il était une fois une modeste petite ville de banlieue… Au coeur de grandes cités HLM se dresse un espace clair et vitré, visible de très loin, nous pourrions l'appeler un auditorium. Dans ce lieu vivaient des instruments de musique. Chacun jouait sa partition, s'essayant à quelques duos ou trios, mais sur de brèves oeuvres, ils travaillaient surtout la musique du corps. Un peu plus loin dans la ville et dans les communes environnantes, vivaient d'autres orchestres, très spécialisés. Certains connaissaient bien la musique de l'esprit et du coeur, d'autres celle du social, d'autres celle de l'école ou de la crèche… Mais ils se fréquentaient peu.

Flexible beam structure is usually applied in various fields of engineering and industrial. There are few points of interest using flexible structure and one of the advantages is that its lighter compared to a rigid structure. Besides that, flexible beam also can save cost, reduce energy consumption, and improve operation safety. However, flexible beam structures are too sensitive and susceptible to with unwanted vibration that would cause damage or degradation to the structure system. Hence, to overcome the problem, appropriate modelling and controller for such systems should be developed. Currently, there are plenty of methods that have been developed by researchers to suppress undesired vibration. Based on previous studies, most researchers nowadays use system identification (SI) as a modelling technique to develop a dynamic model of flexible structure via swarm intelligence algorithm (SIA). Therefore, two type of algorithms was used in this work for modelling development of flex...

Abstract. In the paper, we try to provide a comprehensive look on a multi-objective design of radiating, guiding and reflecting structures fabricated both from special materials (semiconductors, high-impedance surfaces) and conventional ones (microwave ...

This paper proposes a hybrid approach of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for the mobile Radio Frequency Identification System (RFID) reader to get the shortest path for object localization. In this approach, we have adopted the ACO global pheromone updating information of ants to guide the update velocities and position for PSO based on nearest neighbor constraints. The pheromone information is used efficiently to guide the selection of each particle in a search space of its visits. The best path will be used for mobile RFID reader for objects localization in search space. Simulation results show that the method is effective, minimizing the number of visited nodes for a mobile RFID reader.

A flexible beam is recognized as a lightweight structure that is prone to excessive vibration, resulting in poor performance. Thus, controlling unwanted vibration is necessary to maintain the system's performance. Therefore, this study presents a technique to suppress undesired vibration in a flexible beam structure by introducing active vibration control (AVC). However, to develop an effective controller, an appropriate flexible beam model must first be obtained. In recent times, one of the best methods employed to model a flexible beam structure is system identification via a swarm intelligence algorithm. In this study, an intelligent algorithm acknowledged as cuckoo search (CS) was acquainted. The capability of the proposed algorithm was verified using three robustness techniques which were correlation test, pole-zero diagrams and mean square error (MSE). The simulation result showed that the CS algorithm achieved superior performance by achieving the lowest MSE of 6.1547x10-9 , a correlation test between a 95% confidence level and high stability. Next, a proportionalintegral-derivative (PID) controller tuned by the Ziegler-Nichols method was developed using the transfer function accomplished from the CS model. Two types of interference, namely single and multiple sine waves were introduced to validate the effectiveness of the controller. The controller successfully achieved a 30.2 dB of attenuation level for both disturbances.

Le cadre de cet article s'inscrit dans un contexte d'évolutions majeures que traversent actuellement les organisations en générant une dégradation des conditions de travail, portant parfois atteinte à la santé des personnes. Parmi les différentes formes de délitement des relations professionnelles, nous nous intéressons, dans cette recherche, aux conflits de nature relationnelle. Cet article traite du rôle déterminant des besoins insatisfaits dans les situations de conflits relationnels réalistes (au sens de Simmel, 1992). C'est parce que la satisfaction des besoins des uns obère la satisfaction des besoins des autres que les conflits éclatent. La difficulté de la résolution de ces conflits tient au fait que la cause révélée n'est que très rarement la cause réelle du conflit. Celle-ci reste le plus souvent cachée ou non conscientisée, même par l'intéressé lui-même. Le cadre conceptuel s'arrêtera notamment sur la nature de ces besoins cachés et non satisfaits qui « mettent le feu », parfois avec beaucoup de violence, à des relations interindividuelles. Il montrera aussi que le manque de reconnaissance, le sentiment d'insécurité et le sentiment d'exclusion constituent les dénominateurs communs de bon nombre de ces conflits. Nous en ferons la démonstration à travers une étude de cas réelle anonymée issue d'une observation participante. Le cadre conceptuel retenu nous place délibérément dans une approche normative qui autorisera certaines préconisations qui seront apportées autour de la notion de réparation symbolique.

Route planning for multiple destinations via a railway system (RS) is challenging, especially in a complex network with hundreds of stations and interchanges, resulting in a railway traveling salesman problem (RTSP), which is a variant of the traveling salesman problem (TSP). Limited attention has been devoted to solving the RTSP, despite the increase in the number of people using RSs and the added complexity of network expansions. An optimization algorithm and mathematical model based on the foraging behavior of bees and decision theory were used in this paper to identify the optimum RS route to multiple destinations before returning to the first station. Data collected from RSs in Japan and Malaysia were used to create 200 test cases (100 cases with each dataset), and the results were compared to specific solutions and the official optimum route planner to prove that the model is a promising approximation method. The solutions were evaluated and verified by comparing results from another 200 brute-force cases generated by the Wiley TSP Solver. The results obtained from the experiments prove the reliability and capability of the route planning and optimization solutions for RSs with different complexities and in different environments without the assistance of information technology.

Route planning for multiple destinations via a railway system (RS) is challenging, especially in a complex network with hundreds of stations and interchanges, resulting in a railway traveling salesman problem (RTSP), which is a variant of the traveling salesman problem (TSP). Limited attention has been devoted to solving the RTSP, despite the increase in the number of people using RSs and the added complexity of network expansions. An optimization algorithm and mathematical model based on the foraging behavior of bees and decision theory were used in this paper to identify the optimum RS route to multiple destinations before returning to the first station. Data collected from RSs in Japan and Malaysia were used to create 200 test cases (100 cases with each dataset), and the results were compared to specific solutions and the official optimum route planner to prove that the model is a promising approximation method. The solutions were evaluated and verified by comparing results from another 200 brute-force cases generated by the Wiley TSP Solver. The results obtained from the experiments prove the reliability and capability of the route planning and optimization solutions for RSs with different complexities and in different environments without the assistance of information technology.

Travelling salesman problem (TSP) is a most popular combinatorial routing problem, belongs to the class of NP-hard problems. Many approacheshave been proposed for TSP.Among them, swarm intelligence (SI) algorithms can effectively achieve optimal tours with the minimum lengths and attempt to avoid trapping in local minima points. The transcendence of each SI is depended on the nature of the problem. In our studies, there has been yet no any article, which had compared the performance of SI algorithms for TSP perfectly. In this paper,four common SI algorithms are used to solve TSP, in order to compare the performance of SI algorithms for the TSP problem. These algorithms include genetic algorithm, particle swarm optimization, ant colony optimization, and artificial bee colony. For each SI, the various parameters and operators were tested, and the best values were selected for it. Experiments oversome benchmarks fromTSPLIBshow that artificial bee colony algorithm is the best one among ...

Ultra high frequency (UHF) and very high frequency (VHF) bands are widely used with near ground applications especially for communication purposes. However, due to the limited antenna height, the VHF/UHF signals are very sensitive to the surroundings. The signal may attenuate, fade or loss depending on the condition of the environment. Therefore, it is a challenging task to find the optimal values for network topology planning. In this paper, three multi-objective algorithms namely NSGA-II, SPEA-II and OMOPSO are considered to mitigate the problem. This paper also intends to maximize the electromagnetic fields and signal propagation. On the other hand, it intends to minimize path loss and signal attenuation. Different environment settings such as diverse foliage depth and tree trunk height are considered to evaluate the proposed model. From the experiments, it is shown that NSGA-II outperforms other algorithms. The experiment also shows that the optimal foliage depth between sender and receiver is less or equal to 2 km and the optimal tree trunk height is less or equal to 7 m.

Mutation is one of the most important stages of the genetic algorithm because of its impact on the exploration of global optima, and to overcome premature convergence. There are many types of mutation, and the problem lies in selection of the appropriate type, where the decision becomes more difficult and needs more trial and error. This paper investigates the use of more than one mutation operator to enhance the performance of genetic algorithms. Novel mutation operators are proposed, in addition to two selection strategies for the mutation operators, one of which is based on selecting the best mutation operator and the other randomly selects any operator. Several experiments on some Travelling Salesman Problems (TSP) were conducted to evaluate the proposed methods, and these were compared to the well-known exchange mutation and rearrangement mutation. The results show the importance of some of the proposed methods, in addition to the significant enhancement of the genetic algorith...

Optimization of active power loss in Electrical Power systems is complicated because of large, complex, and geographically widely distributed power systems. It is advisable to use the most efficient optimization technique based on its suitability to find an optimized solution of the problem. Active power loss minimization in a system is obtained by controlling the flow of reactive power. The reactive power flow control can be achieved through generator bus voltage, transformer tappings and shunt capacitor banks. An overview of different artificial intelligence (AI) optimization techniques used in power optimization problems are discussed in this paper. Hybrid or improved AI techniques having peculiar characteristics are also presented. This paper studies different techniques implemented for active power loss minimization.

This paper presents a discrete particle swarm optimization (DPSO) algorithm with heterogeneous (non-uniform) parameter values for solving the dynamic travelling salesman problem (DTSP). The DTSP can be modelled as a sequence of static sub-problems, each of which is an instance of the TSP. We present a method for automatically setting the values of the DPSO parameters without three parameters, which can be defined based on the size of the problem, the size of the particle swarm, the number of iterations, and the particle neighbourhood size. We show that the diversity of parameter values has a positive effect on the quality of the generated results. We compare the performance of the proposed heterogeneous DPSO with two ant colony optimization (ACO) algorithms. The proposed algorithm outperforms the base DPSO and is competitive with the ACO.