Abstract:

Several heuristic algorithms for constrained redundancy optimization in complex systems have been proposed, giving solutions that are optimal in 1-neighborhood (mostly) or 2-neighborhood. Perhaps the most interesting and efficient heuristic algorithm is that given by Agarwal and Aggarwal [9] giving solutions that are optimal in 3-neighborhood. In this paper an improved 3-neighborhood heuristic algorithm is proposed. Suitable sensitivity factors are defined to search for optimal / near optimal solution. The algorithm is tested for 8 sets of problems (with linear constraints) each with 10 randomly generated data and, 5-unit bridge structure with nonlinear constraints. Computational results illustrate its effectiveness showing an overall improvement both in solution quality and computing time. As such the heuristic proposed is attractive and can be easily and efficiently applied to numerous real life systems.
Received on August 20, 2005
References: 11