The world is replete with all kinds of complex systems, be they ecological, social, economic, or political. Nevertheless, complex systems share several common characteristics. First, they are thermodynamically open, meaning that they exchange energy and/or mass with their environment. Second, they are often composed of a large number of diverse components. Third, system components interact with...

In this paper, we provide a general purpose simulation framework for complex adaptive systems. Our framework will deal with a number of important criteria including self-organization, emergence, and others. We then show that the framework can capture the common underlying structure of complex adaptive systems through demonstrating its application in specific biological domains.

In this paper, a decentralized group formation algorithm for task allocation in complex adaptive systems is proposed. Compared with current related works, this decentralized algorithm takes system architectures into account and allows not only neighboring agents but also indirect linked agents in the system to help with a task. A system adaptation strategy is also developed for discovering effe...

Biology-Inspired techniques for Self-Organization in dynamic Networks (BISON) is a three-year Shared-Cost RTD Project (IST-2001-38923) funded by the Future and Emerging Technologies initiative of the Information Society Technologies Programme of the European Commission. It runs from January 2003 until December 2005. The objective of BISON is the design and implementation of algorithms for manag...

Adaptive reuse offers significant opportunities for energy efficiency and sustainability in the built environment. Design of energy-efficient and high-performance adaptive reuse requires that building performance and simulations tools are used and integrated with the design process. The objectives of this research is to provide building researchers and practitioners with a better understanding ...

Operation of multi-reservoir systems is known as complicated and often large-scale optimization problems. The problems, because of broad search space, nonlinear relationships, correlation of several variables, as well as problem uncertainty, are difficult requiring powerful algorithms with specific capabilities to be solved. In the present study a Self-adaptive version of Melody Search algorith...

In this paper, a genetic algorithm (GA) is proposed as a search strategy for not only positive but also negative quantitative association rule (AR) mining within databases. Contrary to the methods used as usual, ARs are directly mined without generating frequent itemsets. The proposed GA performs a database-independent approach that does not rely upon the minimum support and the minimum confide...

In this paper we present a genetic algorithm-based heuristic for solving the set partitioning problem (SPP). The SPP is an important combinatorial optimisation problem used by many airlines as a mathematical model for flight crew scheduling. A key feature of the SPP is that it is a highly constrained problem, all constraints being equalities. New genetic algorithm (GA) components: separate fitn...