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A population diffusion algorithm for energy-efficient distributed flexible job shop scheduling problem
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DOI：10.1016/j.asoc.2026.115056.png)
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Abstract
En 中文
• A relaxation factor is introduced in environmental selection to reduce convergence pressure in the evolutionary process. • Comprehensive heuristics guide local search, acting broadly on the population and precisely on elite archive. • Computational resources are dynamically allocated to balance convergence and diversity. • Experiments validate the algorithm’s superior performance.
Keywords:
relaxation factor
comprehensive heuristics
dynamic resource allocation
energy-efficient scheduling
distributed flexible job shop scheduling
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