Hybrid Pattern Search-Quantum Optimization Method for Engineering Optimization Problems

Abstract

Abstract The Quantum-Based Optimisation Method (QBOM) is a novel optimization approach based on quantum computing concepts. The novel optimization method's durability is studied using its capacity to conjoin with existing optimization techniques. This study uses The QBOM with the Pattern Search (PS) technique to solve engineering optimization problems. The first strategy, Hybrid I, uses QBOM for global search optimization, followed by PS searching in the nearby region for the optimum solution. The second strategy, Hybrid II, uses QBOM as a local search optimization within Pattern Search. In each iteration, QBOM starts searching inside PS for a better solution than the one detected at that stage, which is labelled as PS's new search point. These two hybrid techniques attempt to expand the possibilities of QBOM's local search mechanism while demonstrating its resilience. The hybridised methodologies are used to solve benchmark optimization problems and six real-world engineering optimization problems. The study revealed that the two hybrid techniques worked brilliantly, producing solutions that exceeded previous methods described in the literature for certain benchmark optimization problems. Not only did the hybridised methods produce better results in less computational time, but they also demonstrated that QBOM could be used to improve the search mechanism and accelerate the performance of the evolutionary algorithm in the local search to match its execution in the global search.