Pages that link to "Item:Q2664442"
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The following pages link to Energy aware scheduling in flexible flow shops with hybrid particle swarm optimization (Q2664442):
Displaying 15 items.
- Energy-aware real-time task scheduling for heterogeneous multiprocessors with particle swarm optimization algorithm (Q1718052) (← links)
- A new energy-aware flexible job shop scheduling method using modified biogeography-based optimization (Q1993083) (← links)
- Exact method to optimize the total electricity cost in two-machine permutation flow shop scheduling problem under time-of-use tariff (Q2147073) (← links)
- \(N\)-NEH+ algorithm for solving permutation flow shop problems (Q2668738) (← links)
- Optimal foraging algorithm for multi-objective hybrid flow shop scheduling problem (Q3385720) (← links)
- (Q5383440) (← links)
- Multi-objective energy-efficient hybrid flow shop scheduling using Q-learning and GVNS driven NSGA-II (Q6047920) (← links)
- Loads scheduling for demand response in energy communities (Q6068684) (← links)
- Energy-aware production scheduling in the flow shop environment under sequence-dependent setup times, group scheduling and renewable energy constraints (Q6109801) (← links)
- Job scheduling under time-of-use energy tariffs for sustainable manufacturing: a survey (Q6112694) (← links)
- A systematic review of multi-objective hybrid flow shop scheduling (Q6112731) (← links)
- Multi-objective optimization of energy-efficient production schedules using genetic algorithms (Q6159491) (← links)
- Production planning under RTP, TOU and PPA considering a redox flow battery storage system (Q6179224) (← links)
- A hybrid genetic algorithm based on reinforcement learning for the energy-aware production scheduling in the photovoltaic glass industry (Q6551123) (← links)
- A smart energy scheduling under uncertainties of an iron ore stockyard-port system using a rolling horizon algorithm (Q6551130) (← links)
