13 research outputs found
Modelling the migration and maturation of dendritic cells for automatic optimization of complex engineering problems
Artificial Immune Systems - ICARISThe metaphor of Migration and Maturation of Dendritic Cells (DCs), in particular, the induced signal pathways to the change of the immunogenic functions of DCs (Martin-Fontecha, Lanzavecchis & Sallusto, 2009) provides important features for the development of the proposed DC-inspired optimization algorithm. Specifically, the quantified capability and behavioral change of DCs (Callard, George & Stark, 1999) of the classical DC models (Caetano Reis, 2006), namely, (i) ontogeny of DC, (ii) the selectively up-regulation of markers (of DC subsets), (iii) the level of threat (of the antigen), (iv) production of chemokine and cytokine, (v) transcription factors, and (vi) the effector functions of DCs underpin a highly autonomous control mechanism for the evolution of the optimal solution(s).link_to_OA_fulltex
An immune inspired algorithm for solving dynamic vehicle dispatching problems in a port container terminal
An optimisation framework of dendritic cells
Congress Theme: Immunology without Borders!Oral Presentations Session 3The paradigm of a signal cascading network of Dendritic Cells (DCs) underpins T-cells priming in the human immune system, which is one of the critical cell-mediated components in the innate immunity. This study is motivated by the immunological behavior of DCs, intracellular signal processing, and the architecture of the aforementioned signaldriven network in the maturation and migration processes. In parallel with these immuno-features and problem-solving techniques, a distributed DC-inspired framework is developed for resolving optimization problems. In the context of the study, the capabilities of the proposed framework are experimented in a small-scale resources scheduling problem. As of the obtained results, sets of high-quality solutions are produced, which also provide significant insights for the further development of DCmediated framework as presented in this paper
Immune-inspired framework for dynamic vehicle dispatching problems in port container terminal
Session E: Maritime - E2-2: no. 213Conference Theme: Unfolding the New Era of Business Collaboratio
A cooperative multi-objective optimization framework based on dendritic cells migration dynamics
Conference Theme: Innovative Techniques and Applications of Artificial IntelligenceSub-title of book: Incorporating Applications and Innovations in Intelligent Systems XX Proceedings of AI-2012, The Thirty-second SGAI International Conference on Innovative Techniques and Applications of Artificial IntelligenceClonal Selection and Immune Network Theory are commonly adopted for resolving optimization problems. Here, the mechanisms of migration and maturation of Dendritic Cells (DCs) is adopted for pursuing pareto optimal solution( s) in complex problems, specifically, the adoption of multiple characters of distinct clones of DCs and the immunological control parameters in the process of signal cascading. Such an unconventional approach, namely, DC-mediated Signal Cascading Framework further exploits the intrinsic abilities of DCs, with the added benefit of overcoming some of the limitations of conventional optimization algorithms, such as convergence of the Pareto Front
AIS based distributed wireless sensor network for mobile search and rescue robot tracking
The General Suppression Control Framework (GSCF) is a framework inspired by the suppression hypothesis of the immune discrimination theory. The framework consists of five distinct components, the Affinity Evaluator, Cell Differentiator, Cell Reactor, Suppression Modulator, and the Local Environment. These reactive components, each responsible for a specific function, can generate long-term and short-term influences to other components by the use of humoral and cellular signals.This paper presents the design and application of a GSCF based distributed wireless sensor network prototyping system for tracking mobile search and rescue robots. The main objective of this physical prototyping system is to demonstrate the possibility of applying advanced Zigbee sensors to form a network that can locate a small group of mobile robots within the wireless sensor network. Another important objective of the prototyping system presented is to identify potential technological constraints in the physical system. Referencing to the result obtained, future research can be formulated and realistic simulation environment can be developed. © 2008 Springer-Verlag Berlin Heidelberg.link_to_subscribed_fulltex
AIS based distributed wireless sensor network for mobile search and rescue robot tracking
This research presents the implementation of GSCF, an AIS-based control framework, on a distributed wireless sensor network for tracking search and rescue robots in open fields. The General Suppression Control Framework (GSCF) is a framework inspired by the suppression hypothesis of the immune discrimination theory. The framework consists of five distinct components; each carries a specific function that can generate long-term and short-term influences to other components by the use of humoral and cellular signals. The goal of the research is to develop mathematical models that can assist the control and analyses of robots behavior through the use of Suppressor Cells in the Suppression Modulator. Acquire data from the physical robot will be used as simulation parameters in future search and rescue research. © 2009 Springer Science+Business Media B.V.link_to_subscribed_fulltex
AIS-based distributed wireless sensor network for mobile search and rescue robot tracking
LNCS v. 5132 entitled: Artificial Immune Systems: 7th International Conference, ICARIS 2008, Phuket, Thailand, August 10-13, 2008. ProceedingsThe General Suppression Control Framework (GSCF) is a framework inspired by the suppression hypothesis of the immune discrimination theory. The framework consists of five distinct components, the Affinity Evaluator, Cell Differentiator, Cell Reactor, Suppression Modulator, and the Local Environment. These reactive components, each responsible for a specific function, can generate long-term and short-term influences to other components by the use of humoral and cellular signals.This paper presents the design and application of a GSCF based distributed wireless sensor network prototyping system for tracking mobile search and rescue robots. The main objective of this physical prototyping system is to demonstrate the possibility of applying advanced Zigbee sensors to form a network that can locate a small group of mobile robots within the wireless sensor network. Another important objective of the prototyping system presented is to identify potential technological constraints in the physical system. Referencing to the result obtained, future research can be formulated and realistic simulation environment can be developed. © 2008 Springer-Verlag Berlin Heidelberg
An immune inspired algorithm for solving dynamic vehicle dispatching problem in a port container terminal
LNCS v. 5666 entitled: Artificial Immune Systems: 8th International Conference, ICARIS 2009, York, UK, August 9-12, 2009. ProceedingsA typical Vehicle Dispatching Problem (VDP) for a port container terminal often involves offline resource allocation and is often successfully solved by heuristics algorithms. In this research, an autonomous and decentralized vehicle dispatching algorithm is proposed in which the algorithm is inspired by the human immune system. Specifically, the proposed algorithm is inspired by the cell-mediate immune response of T-cells that possess the capability of exploring the environment and providing an adaptive and specific immune response to the invading antigens. We conduct extensive simulation studies to study the performance of the algorithm in solving a typical vehicle dispatch problem derived from realistic terminal configurations and operational constraints. The results show good vehicle utilization and low computational cost when comparing with a GA-based algorithm. © 2009 Springer.link_to_subscribed_fulltex