A distributed permutation flow-shop considering sustainability criteria and real-time scheduling

Keyphrases

• Adaptation 33%
• Benders Decomposition 33%
• Consumption Reduction 33%
• Distributed Permutation Flowshop 100%
• Distributed Permutation Flowshop Scheduling 33%
• Dynamic Environment 33%
• Dynamic Scheduling 33%
• Energy Consumption 33%
• Event-driven Rescheduling 33%
• Heuristic Algorithms 33%
• Integrated Sustainability 33%
• Job Opportunities 33%
• Lagrangian Relaxation 33%
• Lost Workdays 33%
• Makespan Minimization 33%
• Mixed Integer Programming Model 33%
• Model Applicability 33%
• Model Complexity 33%
• Permissible Limit 33%
• Predictive-reactive 33%
• Predictive-reactive Scheduling 33%
• Proactive-reactive Scheduling 33%
• Problem-specific Heuristic 33%
• Production Scheduling 66%
• Real-time Scheduling 100%
• Real-time Scheduling Strategy 33%
• Recent Advancements 33%
• Scheduling Strategy 33%
• Simulated Annealing Search 33%
• Sustainability Criteria 100%
• Sustainable Production 66%
• Tabu Search 33%
• Valuable Insight 33%

Engineering

• Applicability 50%
• Flowshop Scheduling 50%
• Lagrangian Relaxation 50%
• Mixed-Integer Programming Model 50%
• Reducing Energy Consumption 50%
• Reformulation 50%
• Scheduling Strategy 100%
• Sustainable Production 100%

Computer Science

• Case Study 25%
• Dynamic Environment 25%
• Energy Consumption 25%
• Flowshop Scheduling 25%
• Lagrangian Relaxation 25%
• Metaheuristic Algorithm 25%
• Mixed Integer Programming 25%
• Model Complexity 25%
• Production Scheduling 25%
• Programming Model 25%
• Real Time Scheduling 100%
• Scheduling Problem 25%
• Scheduling Strategy 50%
• Simulated Annealing 25%
• Tabu Search 25%