Improved Jaya Algorithm for Solving No-Wait Distributed Scheduling Problems

This study presents an enhanced Jaya algorithm for addressing distributed no-wait flowshop scheduling problems with the objective of minimizing the maximum completion time (makespan). First, a novel hybrid initialization strategy is proposed, integrating the Nawaz-Enscore-Ham (NEH) heuristic with a problem-specific job allocation mechanism to generate a high-quality initial population. To maintain population diversity and enhance solution quality during evolution, the algorithm employs a dynamic combination of insertion and swap operators, complemented by a jigsaw puzzle-inspired algorithm recombination mechanism. Further, an acceleration strategy is introduced to expedite convergence, while a tailored local search procedure, leveraging problemspecific knowledge, is embedded to intensify exploitation capabilities. Finally, the simulation results are compared with the existing algorithms to verify the effectiveness of the proposed algorithm.