Observation On Quality & Quantity Of Aggregate Content In Concrete Mix Design By Adding Fly Ash Based Geopolymer

This Research paper work proposes application and better implementation of artificial immune system approach so that it enables to develop an algorithm for optimizing multi-objective problems. The main objective of this research is to analyze and enhance the artificial immune system approach for developing an algorithm to solve various real life based engineering multi-objective optimizing problems. This algorithm will be used to optimize multi objective problems. The main idea of algorithm is adopted and derived from the biological system of immune. The focus for choosing the artificial immune system to develop algorithm was, if an adaptive pool of antibodies can produce intelligent behavior, then we can use this power of computation to point out the problems. This artificial immune system algorithm makes use of mechanism of vertebrate immune system along with clonal selection principle. This model presents crossover mechanism which is integrated into traditional immune system algorithm based on clonal theory. The Algorithm is proposed with the value of real parameters in spite of binary coded parameters. Only non-dominated individual and best feasible antibodies will added. All the individuals in memory set will be cloned. In this work a novel artificial immune system algorithm is proposed. The proposed algorithm is then further implemented to solve real life engineering multi objective optimizing problems. Not only one solution, but, preferred multi sets of solutions near the reference point are found. We can minimize and maximize complex multi objective optimizing problems where both the objectives can best meet and none of the objective can bypass other objective. This algorithm will guide search for the global Pareto optimal front and maintains the solution diversity. Biological Info-system basically classified into the systems like Endocrine System, Nervous System, Genetic System, and Immune System. Biological Info-processing-systems have further many more interesting functions and are also expected to give various feasible ideas for engineering fields, Industrial Control Systems, Pattern recognition, Information encryption, Robotics, Network security, Intrusion detection and further more. Artificial Immune System is a type of system which is developed on the basis of the current understanding of the immune system. It is also consists of various properties like diversity, distributed computation, self-monitoring, cache coherence, dynamic learning and error tolerance. In fact the Artificial Immune System is inspired by immunology, immune functions, observed many biological principles and their models, which may applied for complex problems.