What question did this study set out to answer?

The study aims to improve energy-efficient production scheduling in a flexible flow shop using a hybrid approach.

Energy‐aware scheduling in a flexible flow shop using a hybrid constraint programming approach

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Investigates energy-efficient scheduling in a flexible flow shop, integrating advanced energy flexibility strategies and optimization methods.

The study aims to improve energy-efficient production scheduling in a flexible flow shop using a hybrid approach.
Integrated energy strategies from multiple sources including grid electricity and photovoltaics.
Implemented a demand bidding mechanism for curtailment capacity during power system stress.
Investigated a mixed integer linear programming model alongside a hybrid constraint programming approach.
Conducted computational experiments and benchmark comparisons using various optimization methods.
The hybrid method achieved solutions with a relative gap below 1% across all instance sizes.
Results demonstrate that the hybrid approach consistently outperforms other strategies in solution quality.
Metaheuristic approaches remained competitive regarding computation time, with small relative gaps.

Mhanna et al. (2026) studied this question.

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Investigates energy-efficient scheduling in a flexible flow shop, integrating advanced energy flexibility strategies and optimization methods.