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Utilizing Distributed Generators (DGs) and Energy Storage Systems (ESSs) enhances power system reliability, drawing significant research attention. However, these systems pose challenges, compelling scientists to explore optimization methods. Our paper presents an innovative solution, Parallel Multi-Objective Multi-Verse Optimization (PMOMVO), aimed at optimizing DGs and Battery Energy Storage Systems (BESSs) allocation. This optimization addresses voltage violations and operation costs, crucial concerns for system operators and consumers. By leveraging a parallel approach, PMOMVO significantly accelerates the optimization process. We compared its results with a base case scenario, demonstrating the superior efficiency of our parallel method. It not only enhances the optimization performance but also proves its efficacy by generating optimal solutions from the Pareto front set. This research showcases the benefits of PMOMVO, offering a faster, more efficient, and reliable way to optimize power systems, benefiting both operators and consumers. • Introduces a novel bi-level optimization approach for DG and BESS allocation and operation. • Proposing a multi-objective formulation to identify Pareto optimal solutions, offering a balance between voltage stability and cost-effectiveness. • Optimizes asset operation strategies, considering both peak and off-peak load times, enhancing resource utilization. • Proposes a parallel processing method based on modified MOMVO, significantly accelerating computations for large distribution systems problems. • Achieves a substantial improvement in the speed-up index, ensuring swift and effective DG and BESS allocation and operation in complex systems. [ABSTRACT FROM AUTHOR]