Abstract
PurposeThis paper aims to focus on solving highly constrained redundancy optimization problems in binary complex systems.Design/methodology/approachThe proposed algorithm searches a possibly improved solution in the k‐neighborhood (k≥2) of the current best feasible solution, by adding one unit in a selected subsystem and eliminating one from some other subsystem(s).FindingsThe algorithm is tested on complex system structures from the literature by solving a set of problems (with both linear and non‐linear constraints), with given and randomly generated data. It is observed that, compared with the other existing heuristics, there is much overall improvement in various performance measures.Practical implicationsThe proposed algorithm is a better alternative and can be easily and efficiently applied to numerous real life systems such as computer and communication systems, telecommunication networks, automobile, nuclear and defense systems etc., giving optimal/near‐optimal solutions.Originality/valueResearchers in reliability optimization have placed emphasis on heuristic approaches. The paper presents a new heuristic algorithm for solving the constrained redundancy optimization problems in complex binary systems.
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