A comprehensive survey on cultural algorithms

Peer reviewedPostprin

人・ユーザー中心の移動サービスと群集マネジメントのためのモデリング，シミュレーションと最適化

Tohoku University博士（情報科学）thesi

Intelligent Control of Solar LED Street Lamp Based on Adaptive Fuzzy PI Control

As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities

Algorithms for the multimodal transportation problem

Orientadores: Akebo Yamakami, Priscila Cristina Berbert RampazzoDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Neste trabalho, foi explorado o problema de encontrar rotas mínimas em uma rede de transporte multimodal. Condições reais de roteirização incluem múltiplos modais (carro, bicicleta, metrô, ônibus, trem etc.) e múltiplos tomadores de decisão, cada um com diferentes objetivos. Esta consideração nos remete a uma proposta multiobjetivo, pois interesses bastante comuns como custo financeiro e tempo de viagem podem ser conflitantes. Foram implementados quatro propostas de resolução do Problema de Transporte Multimodal com Otimização Multiobjetivo. Três delas consideram os múltiplos objetivos através do Método das Ponderações: uma utiliza um solver de Programação Linear e as outras duas são adaptações de algoritmos clássicos de Caminho Mínimo para redes multimodais. A quarta proposta trata-se de um Algoritmo Genético Multiobjetivo que manipula simultânea e explicitamente os múltiplos objetivos. Todas as propostas elaboradas têm como solução um conjunto de caminhos possíveis, e a escolha do melhor caminho deve ser feita pelo usuário de acordo com suas preferências. Para auxiliar na tomada de decisão do usuário, foi implementado um Modelo de Otimização Multi-critério baseado na metodologia de Análise Envoltória de Dados. Ele avalia a eficiência das soluções obtidas na abordagem multiobjetivo, com a inserção de novos critérios de avaliação do caminho como sustentabilidade, conforto e segurançaAbstract: This study aims to explore the Shortest Path Problem between two points in a multi-modal network. In real routing conditions, it includes many means of transportation (car, bicycle, subway, train, etc) and many decision makers. This situation forward to an multi-objective approach. The most common objectives to find a best route are the time travel and the financial cost and they are often conflicting. This work implements four proposals to solve the Multi-modal Transportation Problem with a Multi-objective Optimization. Three of them consider the multiple objectives with Weighted Sum Model: one uses a Linear Programming solver and two others uses an adaptation of classical Shortest Path Problem algorithms for a multi-modal network. The last proposal is a Multi-objective Genetic Algorithm that takes into account many objectives of the problem simultaneously. All the implementations give as result a set of solutions. The decision maker needs to choose the best route that fits with her/his preference. Therefore, we developed a Multi-criteria Optimization Model based on Data Envelopment Analysis to help the costumer. This model allows measure the efficiency of the solutions with new criteria such as sustainability, well-being and safety of the routeMestradoAutomaçãoMestra em Engenharia Elétrica133528/2016-2CNP

最適化問題に対するブレインストーム最適化アルゴリズムの改善

富山大学・富理工博甲第170号・于洋・2020/3/24富山大学202

Evolutionary Computation 2020

Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms

DESIGN AND DEVELOPMENT OF A SMART ADVISORY SYSTEM FOR HAZARDOUS MATERIALS TRANSPORTATION RISK ANALYSIS VIA QUANTITATIVE APPROACHES

Safe transportation of hazardous materials is critical as it has a high potential of catastrophic accidents depending on the amount of transported product, its hazardous characteristics and the environmental conditions. Consequently, an efficient, smart and reliable intervention is essential to enhance prediction on the impacts of transportation hazards. Although various risk assessment techniques have been used in industry and regulatory bodies, they were developed for evaluating risk of hazardous materials for fixed installation cases instead of moving risk sources. This study applies the Transportation Risk Analysis (TRA), which is an extension of a well-known Quantitative Risk Analysis (QRA) technique in developing and design a Smart Advisory Systems (SAS), to determine the safest routes for transportation of hazardous materials according to Malaysia scenario

Full Proceedings, 2018

Full conference proceedings for the 2018 International Building Physics Association Conference hosted at Syracuse University