The major goal of IJBIC is the publication of new research results on bio-inspired computation methods and their applications. IJBIC provides the scientific community and industry with a vehicle whereby ideas using two or more conventional and computational intelligence based techniques can be discussed.Bio-inspired computation is an umbrella term for different computational approaches that are based on principles or models of biological systems. This class of methods, such as evolutionary algorithms, ant colony optimisation, and swarm intelligence, complements traditional techniques in the sense that the former can be applied to large-scale applications where little is known about the underlying problem and where the latter approaches encounter difficulties. Therefore, bio-inspired methods are becoming increasingly important in the face of the complexity of today's demanding applications, and accordingly they have been successfully used in various fields ranging from computer engineering and mechanical engineering to chemical engineering and molecular biology.IJBIC is especially intended for furthering the overall understanding of new algorithms simulated with various bio-phenomena beyond the current focus, i.e. genetic algorithms, Tabu search, etc. Its objective is improvement in theory and applications of the bio-computation field. Algorithms should therefore be carefully designed and appropriately analysed, and authors are encouraged to assess the statistical validity of their results whenever possible.IJBIC的主要目标是发表关于生物启发计算方法及其应用的新研究成果。IJBIC为科学界和工业界提供了一个载体，在这个载体上可以讨论使用两种或多种基于传统和计算智能技术的想法。生物启发计算是基于生物系统原理或模型的不同计算方法的一个总称。这类方法，如进化算法、蚁群优化和蜂群智能，是对传统技术的补充，因为前者可以应用于对基本问题知之甚少的大规模应用，而后者的方法会遇到困难。因此，面对当今高要求的应用的复杂性，生物启发方法变得越来越重要，相应地，它们已经成功地应用于从计算机工程和机械工程到化学工程和分子生物学等各个领域。IJBIC特别旨在进一步全面了解目前重点以外的各种生物现象模拟的新算法，即遗传算法、Tabu搜索等。它的目标是改善生物计算领域的理论和应用。因此，算法应该被精心设计和适当分析，并鼓励作者尽可能评估其结果的统计有效性。