https://rajpub.com/index.php/ijct KHALSA PUBLICATIONS en-US INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 2277-3061 https://rajpub.com/index.php/ijct/article/view/9709 <p>This study addresses the task-scheduling optimization challenges in parallel computing systems using a novel meta-<br />heuristic framework. We analyze the differential evolution in task scheduling and propose an advanced shift-chain</p> <p>methodology to improve the cooperation between scheduling components. The proposed framework introduces a wait-<br />ing time-based neighborhood exploration strategy for handling complex task dependencies, along with two parallel</p> <p>implementation approaches: basic matching vector (MV) parallelization and an event-driven strategy. The experi-<br />mental results demonstrated superior solution quality and computational efficiency compared with existing methods,</p> <p>particularly in large scale problems. The modular design of this framework enables practical applications in modern<br />computing environments.</p> Sirui Mao Masato Edahiro Copyright (c) 2025 Sirui Mao, Masato Edahiro https://creativecommons.org/licenses/by/4.0 2025-03-31 2025-03-31 25 1 24 10.24297/ijct.v25i.9709