Title: A modified two-archive evolutionary algorithm for many-objective ecological cascade reservoir operation

Authors: Zichen Wei; Hui Wang; Futao Liao; Shuai Wang

Addresses: School of Information Engineering, Nanchang Institute of Technology, Nanchang – 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang – 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang – 330099, China ' School of Information Engineering, Nanchang Institute of Technology, Nanchang – 330099, China

Abstract: Many-objective optimisation problems (MaOPs) widely exist in real-world applications. Though two-archive2 evolutionary algorithm (Two Arch2) showed good performance in solving MaOPs, its performance highly depends on the update methods of convergence archive (CA) and diversity archive (DA). To further improve the efficiency of updating two archives, this paper proposes a modified two-archive evolutionary algorithm (called MTaEA). Firstly, MTaEA adopts two different strategies to update CA. Then, a new update strategy based on radial projection and parallel distance is designed for DA. To validate the performance of MTaEA, two benchmark sets (DTLZ and MaF) with 3, 5, 10, 15, and 20 objectives are tested. Results show MTaEA obtains competitive performance when compared with six other state-of-the-art approaches. Finally, the proposed MTaEA is applied to many-objective ecological cascade reservoir operation in central China. Simulation results indicate MTaEA still achieves promising performance.

Keywords: many-objective evolutionary algorithms; many-objective optimisation problems; parallel distance; two-archive; cascade reservoir operation; scheduling.

DOI: 10.1504/IJBIC.2024.142561

International Journal of Bio-Inspired Computation, 2024 Vol.24 No.4, pp.223 - 239

Received: 29 Feb 2024
Accepted: 13 Jun 2024
Published online: 08 Nov 2024 *

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