Información de la Revista
Swarm and Evolutionary Computation
Factor de Impacto:

Solicitud de Artículos
To tackle complex real world problems, scientists have been looking into natural processes and creatures - both as model and metaphor - for years. Optimization is at the heart of many natural processes including Darwinian evolution, social group behavior and foraging strategies. Over the last few decades, there has been remarkable growth in the field of nature-inspired search and optimization algorithms. Currently these techniques are applied to a variety of problems, ranging from scientific research to industry and commerce. The two main families of algorithms that primarily constitute this field today are the evolutionary computing methods and the swarm intelligence algorithms. Although both families of algorithms are generally dedicated towards solving search and optimization problems, they are certainly not equivalent, and each has its own distinguishing features. Reinforcing each other's performance makes powerful hybrid algorithms capable of solving many intractable search and optimization problems.

About the journal:
Swarm and Evolutionary Computation is the first peer-reviewed publication of its kind that aims at reporting the most recent research and developments in the area of nature-inspired intelligent computation based on the principles of swarm and evolutionary algorithms. It publishes advanced, innovative and interdisciplinary research involving the theoretical, experimental and practical aspects of the two paradigms and their hybridizations. Swarm and Evolutionary Computation is committed to timely publication of very high-quality, peer-reviewed, original articles that advance the state-of-the art of all aspects of evolutionary computation and swarm intelligence. Survey papers reviewing the state-of-the-art of timely topics will also be welcomed as well as novel and interesting applications.

Topics of Interest:
Topics of interest include but are not limited to: Genetic Algorithms, and Genetic Programming, Evolution Strategies, and Evolutionary Programming, Differential Evolution, Artificial Immune Systems, Particle Swarms, Ant Colony, Bacterial Foraging, Artificial Bees, Fireflies Algorithm, Harmony Search, Artificial Life, Digital Organisms, Estimation of Distribution Algorithms, Stochastic Diffusion Search, Quantum Computing, Nano Computing, Membrane Computing, Human-centric Computing, Hybridization of Algorithms, Memetic Computing, Autonomic Computing, Self-organizing systems, Combinatorial, Discrete, Binary, Constrained, Multi-objective, Multi-modal, Dynamic, and Large-scale Optimization.

Furthermore, the journal fosters industrial uptake by publishing interesting and novel applications in fields and industries dealing with challenging search and optimization problems from domains such as (but not limited to): Aerospace, Systems and Control, Robotics, Power Systems, Communication Engineering, Operations Research and Decision Sciences, Financial Services and Engineering, (Management) Information Systems, Business Intelligence, internet computing, Sensors, Image Processing, Computational Chemistry, Manufacturing, Structural and Mechanical Designs, Bioinformatics, Computational Biology, Mathematical and Computational Psychology, Cognitive Neuroscience, Brain-computer Interfacing, Future Computing Devices, Nonlinear statistical and Applied Physics, and Environmental Modeling and Software.
Última Actualización Por Dou Sun en 2019-12-08
Special Issues
Special Issue on Bio-inspired evolutionary computations and their application (BIC-TA19)
Día de Entrega: 2020-03-01

I. Objective of the Special Issue This special issue aims to collect submissions by two routes: (1) Invited Papers from the selected conference papers after expanding substantially from BIC-TA 2019, and (2) Open Call-for-papers from the research fields of the bio-inspired evolutionary computations and their application. Whatever type of submissions should present in-depth fundamental research contributions either from a methodological perspective or from an application point of view. The 14th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2019) will be held on 22-25, November, 2019, in Zhengzhou, China. BIC-TA 2019 is the fourteenth annual event in the high-reputation BIC-TA series. BIC-TA 2019 aims to provide a high-level international forum for researchers working in the field of bio-inspired computing to present their recent results and to exchange ideas. II. Themes The topics of this special issue include two aspects. First, contributions on bio-inspired evolutionary computations methodologies and theories are very welcome. Second, contributions on applications of bio-inspired evolutionary computations are also welcome. Topics of interest include, but are not limited to: Differential Evolution; Ant Colony Optimization; Artificial Bee Colony; Artificial Life and Artificial Immune Systems; Brain-inspired and Brain-like Computation; Cellular Automata; DNA, Molecular and Membrane Computing; Evolutionary Computation; Hybrid Intelligent Systems; Intelligent Agents; Memetic Computing; Particle Swarm Optimization; Quantum computing; Random Search Technique; Swarm Intelligence; Tabu Search; Other Cross-disciplinary Topics in SI&EC.
Última Actualización Por Dou Sun en 2020-01-04
Special Issue on Advanced Intelligent Optimization Algorithms for Distributed Shop Scheduling
Día de Entrega: 2020-06-30

Along with the development of economic globalization, multi-site production and supply chain integration are not uncommon nowadays. The distributed shop scheduling, which enhances system reliability and utilization of resources through effective allocation of processes and collaboration among multi-sites or supply chains, has attracted the interest of many researchers and practitioners from a variety of disciplines, such as computer science, economics, manufacturing, and service operations management. Intelligent optimization algorithms including genetic algorithm, particle swarm optimization, differential evolution, ant colony optimization, estimation of distribution, artificial bee colony, iterated greedy, iterated local search, taboo search, and many others, have been successfully applied to a variety of distributed scheduling problems as well as the practical systems. This special issue aims to establish a forum for the discussion of recent progresses on the advanced intelligent optimization method for distribution shop scheduling problems. This special issue will publish original research, review and application papers including but not limited to the following fields: Distributed flowshop scheduling Distributed job shop scheduling Distributed parallel machine scheduling Distributed assembly scheduling Distributed flexible manufacturing scheduling Distributed project scheduling Distributed maintenance scheduling Distributed operating room scheduling Distributed energy resources scheduling Distributed vehicle routing problems Distributed multi-objective scheduling Distributed rescheduling Distributed robust scheduling Real-time distributed scheduling Distributed scheduling problems in logistics Distributed planning and scheduling in supply chains Distributed Scheduling in transport, sports, healthcare, engineering, energy management, etc. Other Related Topics
Última Actualización Por Dou Sun en 2019-12-08
Revistas Relacionadas
Conferencias Relacionadas