A Spark-Based Parallel Implementation of Arithmetic Optimization Algorithm

Abstract

Arithmetic optimization algorithm (AOA) is a recent population-based metaheuristic widely used for solving optimization problems. However, the emerging large-scale optimization problems pose a great challenge for AOA due to its prohibitive computational cost to traverse the huge solution space effectively. This article proposes a parallel Spark-AOA using Scala on Apache Spark computing platform. Spark-AOA leverages the intrinsic parallel nature of the population-based AOA and the native iterative in-memory computation support of Spark through resilient distributed datasets (RDD) to accelerate the optimization process. Spark-AOA divides the solutions population into several subpopulations that are distributed into multiple RDD partitions and manipulated concurrently. Simulation experiments on different benchmark functions with up to 1,000-dimension and three engineering design problems demonstrate that Spark-AOA outperforms considerably standard AOA and Spark-based implementations of two recent metaheuristics both in terms of run-time and solution quality.

Research on MPPT control strategy based on CCAOA algorithm

“…et However, being used in the MPPT control system, the algorithm is easy to fall into LMPP and too much oscillation during the search process. To resolve these problems, some researchers put forward a few solutions [21][22][23][24]. The authors (Chtita Smail et al 2023) proposed an MPPT control system using the AOA, the authors proposed an MPPT control system using the AOA, which has higher accuracy and faster convergence speed than the traditional algorithm, but the algorithm is easy tends to fall into LMPP [25].…”

Research on MPPT control strategy based on CCAOA algorithm

“…et However, being used in the MPPT control system, the algorithm is easy to fall into LMPP and too much oscillation during the search process. To resolve these problems, some researchers put forward a few solutions [21][22][23][24]. The authors (Chtita Smail et al 2023) proposed an MPPT control system using the AOA, the authors proposed an MPPT control system using the AOA, which has higher accuracy and faster convergence speed than the traditional algorithm, but the algorithm is easy tends to fall into LMPP [25].…”